Originalscientificpaper

Croat. j. for. eng. 37(2016)1 71

Selecting Evaluation Indices for Cleaner

Production of Plantation Logging in Southern China with Fuzzy Clustering

Methods

Aihua Yu, Tom Gallagher, Chen Zhao, Yao Zhao

Abstract

Over the years, China has shown a significant reduction in natural forest resources, while the increasing area of plantations has made greater contributions to the huge demand for wood. In southern China, these new plantations have produced some problems such as environmen-tal hazards of logging operations and the most reasonable use of forest resources. A new management process called »cleaner production« is defined as reducing pollution from its source, increasing the rate of utilization of resources, and preventing the generation of pollut-ants in the production of services and products. In recent years, cleaner production has been widely applied to industrial processes such as agriculture and other environmental industries. In order to make rational use of plantation resources, to achieve maximum economic effi-ciency and to reduce or remove the environmental hazards of logging operations, it is necessary to carry out an in-depth study of cleaner production on the process of logging operations. This paper aims to establish an index system for cleaner production evaluation of plantation log-ging. The fuzzy clustering method was used to initially screen twenty-nine indices. After screening by the fuzzy clustering method, six first-grade indices and twelve second-grade important indices were selected as formal evaluation indices. The six first-grade indices are 1) cutting area design index, 2) logging operation techniques index, 3) ecological environmental impact index, 4) utilization of resource and energy index, 5) sustainable development index, and 6) safety production management and protection index. A maximum and minimum matrix method and a correlation coefficient matrix method were used to establish the similar matrix in the fuzzy clustering method. The screening results were then compared. The com-parison shows that out of the twelve second-grade indices, ten are similar and two are different. The results suggest that the fuzzy clustering method is reliable for screening indices.

Keywords: plantation, logging operation, cleaner production (CP), evaluation indices, fuzzy clustering method.

tional forest resources inventory in China (2009–2013). Whiletheadditionalplantationharvestinghasmanyeconomicbenefits, ithasalsoproducedsomenewproblemsinsouthernChina,suchassoilerosionandwastetimberintheland.Somecriterianeededtobedevelopedtomeasurewhatisimportantintheperfor-manceoftheseplantations.Thispaperfocusesontheindexsystemforcleanerproduction(CP),whichisanevaluationofplantationlogginginordertorationallyuseplantationresources,achievethemaximumeco-

1. IntroductionWithasharpreductioninthenaturalforestover

thepastdecadeinChina,agreateremphasishasbeenputonplantationstomeetlumberdemand.There-centlycompletedEighthNationalForest Inventorysupportsthisassumption.Specifically,theproportionofplantationharvestinghasincreasedfrom39%to46%,andplantationharvestinghasincreasedto155millioncubicmetersannually(theresultsoftheeighthna-

A. Yu et al. Selecting Evaluation Indices for Cleaner Production of Plantation Logging in Southern China ... (71–87)

72 Croat. j. for. eng. 37(2016)1

nomicbenefit,andreducetheeffectsofloggingontheenvironment.

CPhasbeendefinedin»TheLawofthePeople’sRepublicofChinaonPromotionofCleanerProduc-tion«bycontinuouslyadoptingmeasurestoimprovedesign,usecleanerenergyandrawmaterials,intro-duceadvancedtechniquesandequipment,improvemanagementandmakecomprehensiveuseofresourc-esaswellasothermeasures.CP isalsodefinedbyreducingpollutionfromitssource,increasingtheuti-lizationratioofresources,andreducingorpreventingthegenerationanddischargeofpollutantsduringpro-ductionandinprovidingservices.Thegoalistoallevi-ateoreliminateharmtohumanhealthandtheenvi-ronment(ZhaoandZhang2003).Thisnotonlyappliestoindustrialprocesses,butalsotoagriculture,plan-ning,construction,andservicesasthisisageneralis-sue.Basedon the industrydefinitionofCP and the

characteristicsofplantationlogging,CPinvolvesim-provingcuttingareadesignwiththelocalconditions,usingcleanerenergy,developingreasonableloggingtechnologiesandequipment,improvingmanagementpractices,minimizingpollution,saving,andprotect-ingtheforestryenvironmentandworkers.Theresultsshould be to achieve sustainable plantations. Themethodologyistoproduceamodelforplantationre-sourcesbyusingawholeenvironmentalstrategyfortheprocessesandproductionsofplantationlogginginordertoreduceoreliminateharmtohumanhealthand theenvironmentwhile fullysatisfyinghumanneeds. CPinplantationloggingisanimportantmeansforachievingsustainabilityofplantations.Thefinalgoalistomaximizethebalancebetweennaturalre-sources,energyuseandeconomicbenefitsandmini-mizetheharmtohumansandtheenvironment,allinordertosaveresources,reducewasteandprotecttheenvironmentwhileharvestingtimber.

2. Contents of CP evaluationfor plantation logging

Cuttingareadesign,loggingtechnology,ecologicalenvironmentimpact,resourceandenergyuse,andsustainablebusinessesofforestprotectionandman-agementforworkers,allcontributetotheCP evalua-tionforplantationlogging.Sotheevaluationnotonlyconsidersthelongevity,gradualness,andcomplexityoftheimpactsofloggingonforestecologicalsystems,butalsothemethodandintensityoflogging,scaleofproduction,andthestabilityandrecoveryoftheeco-logicalenvironment.

2.1 Evaluations for cutting area designCPforcuttingareadesignshouldincludethefol-

lowing:designingenergysavingprocesses,promotinglow-energytechniques,shorteningtheworkingtime,simplifyingequipment,andpayingattentiontoen-ergymanagement.Inaddition,usingloggingequip-menttobenefittheecologicalenvironment,reducingloggingwaste and combustiblematerials of forestfires,andimprovingthebenefitsofloggingby-prod-uctswerealsoconsideredwhenevaluatingtheimpor-tance of CP.In designing of an index forCP, the following

shouldbeconsidered:therationalityofloggingpro-cesses(includingthetypeofloggingsystem,indexofloggingintensity,indexofoutturnpercentageandout-put,indexofroaddesign,indexofbucking,indexofskiddingandtransportation,organizationofloggingteamandsoon),advancementofloggingtechnology,reliabilityofpreventativemeasuresforcuttingrenew-ableareas,andoperationmanagementconsiderations.

2.2 Evaluation of logging technologyCutting,skidding,andtransportationarethreeim-

portantprocessesintimberproductiontechnologyinaloggingoperation.Variousworkingmethodsandequipment types areused in eachprocess, so thatmanydifferenttimberproductionmodelsandeco-nomicbenefitscanbecompared.Basedontheinves-tigationofplantationloggingintheFujianProvince,clear-cuttingwas themain typeof cuttingmethod withtheexceptionofthecasesprovidedin»Regula-tionofForestHarvestingandRenew«.Chainsawop-erationwasthemainequipmentmethodoffelling.AngularsawwasonlyusedinafewChinafircollec-tiveforestareaswithmostlysmalldiameterlogs(di-ameter<8cm).Methodsofskiddingincludedaerialcableway,walkingtractor,pushcart,dirtchute,andmanpower.Transportationincludedtruck,farmve-hicle,shipping,andrafting(manpower)(Zhangetal.2008).CPofloggingmainlyreflectedtheinterferenceandacceptabilitytotheenvironment.ReducedImpactLogging(RIL)wasbasedonprinciplesofscienceandengineeringandacombinationofeducationandtrain-ing(Dykstra2001).RILrequiredspecificforestinves-tigationproceduresbeforelogging,includingaplanandconstructionofloggingroadsandlandings,reli-ableways forcuttingandbucking, skidding felledtimbersalongskidroads,skiddingsystemsforpro-tectingsoilandvegetation,andevaluationafterlog-ging. Inaddition,RILalso includedthe impactsofloggingonlandscapes,biodiversity,vegetation,water,andsoil(Long2006).

Selecting Evaluation Indices for Cleaner Production of Plantation Logging in Southern China ... (71–87) A. Yu et al.

Croat. j. for. eng. 37(2016)1 73

Evaluationforloggingmainlyincludesthefollow-ingitems:advanceoftechnology,rationalityofloggingprocesses,coordination,economicbenefits,securityandworkefficienciesofahuman-equipment-environ-mentsystem.Theeconomicbenefitwasbasedonre-ducingworkingcostswhilenotdestroyingthefor-estedecologicalenvironment.

2.3 Evaluation for ecological environment impactsForasmallcuttingarea,soilandvegetationinthe

ecologicalenvironmentwere themostdirectly im-pacted.Whenevaluating loggingpracticessuchascutting,skidding,andtransportation,itbecomesin-creasinglyimportanttoalwaysconsidertheeffectsontheecologicalenvironment.Theunreasonablecutting,skiddingandground

disturbanceimpactmanypartsoftheecologicalenvi-ronmentwhenlogging,includingtheeffectsonsoil,reserve,rivers,biodiversity,loadsofCO2inair,land-scape,andregionalclimate.Therefore,acleanerlog-gingmodelmustminimizetheaboveeffects,inordertomaximizetheecologicalenvironmentalbenefitsoflogging in the forest.

2.4 Evaluation for resources and energy usePlantationswereresourceusedforanevaluation

oflogging.TheforestresourceinChinaisconsideredascarcerawmaterialwhenevaluatingitsbiologicalandeconomicbenefit.So,inordertosaveontheuseofrawmaterialsaswellasmaintainhigherworkingabilityandlevel,largeroutputsandfewerresourcewastesshouldbeexpectatedofplantationlogging.Energyuseintheloggingprocessesmainlymeans

thatfuelandlubricantswereconsumedbyequipmentthatwasusedincutting,skiddingandtransportation.So,low-energyandcleanenergyequipmentshouldbeused.Also,theindexofevaluationforresourceandenergyuseincludedstandingtreeutilization,volumeofwastetimberincuttingarea,volumeofwastetim-berinloadingbay,loggingslashutilization,andthefuelconsumptionofequipmentusedduringlogging.

2.5 Evaluation for sustainable businesses of plantationChinahasimplementednewpracticesinforestry

development,thoughmostlyforafforestation,becauseofmanyfactors.Thesefactorsincludeharvestinginareaswhereforestharvestinghasfollowedthetradi-tionalmethodsandpatterns.Itcanbesaidthatintheseareaswedonotseetheforestforthetrees.Inafforesta-tionareas,someareasweredeforestedwithoutrefor-

estationandhadfalsereporting,whichledtoinac-curateforestresourcedatabase.Thesefactorshaveledto low-quality afforestation, reforestation missingfromtheforesteachyear,andanincreasedimpacttotheenvironmentandecologicalbalance,whichhavecausedirreversibledamagetowoodlandsites.Log-ginghasanimportanteffectontheecologicalenviron-ment,suchasreducingthedepthoflitterfallandde-stroying the surface soil. Especially in spring andsummer,increasedsurfacerunoffusuallyresultsinheavysoilerosion.Moreover,pushingtimberbyskid-dingequipmentnegativelyimpactedthesurfacesoilanddamaged theyoung treesandreserves (Wang1997).Evaluationofplantationsforsustainablebusiness-

esincludedtheutilizationrateofwood,renewablerateofcutoverland,andthesurvivalrateofregenera-tion.TheaimofCPforplantationloggingwassustain-ablebusinesses.

2.6 Evaluation of safety production management and protectionTomakeplantation loggingcleaner,production

mustbecleanerfirst.Thisincludescleanerawarenessandactionoftheproducers.Thiswasparticularlyre-flectedintheaspectsofsafetyonproductionandpro-tection.So,bettereducationofworkerswasthebasisfor achieving CP. If working conditionswere im-proved,employeescouldbenefitfromincreasedsafe-tyandabetteroverallworkingenvironment.

CPcouldminimizetheinjuryrateofoperatorsinworkingprocesses.Meanwhile,CPwasalsofoundtoensureworkerrightsandsafety.OnlylaborprotectionwasabletobecometheessenceofCP.Soforevaluationofsafetyproduction,oneaspectoftheevaluatedcon-tentconsistedofreducingoperationdamageofwork-ersandensuringworkerrightsandsafety.

3. Evaluation indices

3.1 The principles for determining evaluation indicesTheindexsystemforCPevaluationofplantation

loggingconsistsofmanystructuredandgraduatedindicesthatconnectandcomplementeachother.Itisacombinationof theevaluationofsustainableandhighefficientutilizationlevelsofresourcesanditsin-dex,andhowitdirectlyaffectstheresultsofforestresourcesmanagement andutilization levels.Cor-rectlyimplemented,theresultisanaccuraterepresen-tation of CPforplantationlogging.Sustainabledevel-opmenttheoryandecology-economy-societytheory

A. Yu et al. Selecting Evaluation Indices for Cleaner Production of Plantation Logging in Southern China ... (71–87)

74 Croat. j. for. eng. 37(2016)1

weretheguidesforsettinguptheindexsystemfortheCPevaluationofplantationlogging,andtheywerealsobasedonthefollowingfiveprinciples:1)Methodscombinedqualitativeandquantitative

analysis.Inordertoensuretheaccuracyandscientificnature of the results for evaluating the CPofplanta-tions,thequantityindexshouldbeselectedtosetupaquantitativelyevaluablemodel.Ontheotherhand,theevaluatedobjectswerecompletedproductionpro-cessesthatinvolvedvariousquarters.Therefore,theindex systemofCPwasa completedand intrinsicclosed contact system.Absolute quantity, relativequantity,averagesandotherindicescouldbeused,andsomeindicescouldalsobeusedasqualityiftheycouldnotbemanagedbyquantitativeanalysis.2)Independence:thestatusofthesystemcouldbe

describedbyanumberofindices,butintercrossingofinformationalwaysoccurs.Inordertoestablishanindexsystem,representativeandindependentindicesmustbeselectedusingthescientificmethodtoim-proveitsaccuracyandscientificnature.3)Evaluationthroughthewholeprocess:theindex

systemnotonlyincludesthewholeproductionpro-cess,butalsotheproductitself.Inotherwords,CP evaluationsofplantationloggingaimedtoanalyzeandevaluatetherawmaterialandenergyconsump-tion,aswellaspollutantcreationanditstoxicityinthewhole process of design, production, storage, andtransportation.4)Improvingsustainability:CPisasustainableim-

provingprocess,anditrequiresthecompanytocon-tinuouslyachievehigherenvironmentalobjectivesonthebasisofexistingeconomic,technological,anden-vironmental indices.Therefore, for thepurposeofpromotingCP,differentCPobjectivesshouldbese-lected topromote sustainabledevelopmenton thebasisoftheexistingsituation.5)Simpleandfocused: the indexsystemforCP

couldnotcoveralltheprocessesintheplantationlog-ging.Generally,themostsimpleandfocusedindicesareimplementedeffectively.

3.2 Selection of the evaluation indexTheprocessbeginswithselectingsomeevaluation

indices on thebasis of contents andprinciples (asshowninTable1)(Yuetal.2009).Suchindicesshouldnotbecombinedtogetherdirectlybecauseofinforma-tion interference and the fact that this could have an impactontheevaluationresults(Chen2003).Clusteranalysisdividesdataintogroups(clusters)

suchthatsimilardataobjectsbelongtothesameclus-teranddissimilardataobjectstodifferentclusters.The

resultingdatapartitionimprovesdataunderstandingand reveals its internal structure. Partitional clustering algorithmsdivideupadatasetintoclustersorclasses,wheresimilardataobjectsareassignedtothesamecluster,whereasdissimilardataobjectsshouldbelongtodifferentclusters.Inrealapplications,thereisveryoften no sharp boundary between clusters so thatfuzzyclustering isoftenbetter suited for thedata.Membershipdegreesbetweenzeroandoneareusedinfuzzyclusteringinsteadofcrispassignmentsofthedatatoclusters.Fuzzyclusteringisthemethodthatcancapturetheuncertaintysituationofrealdataanditiswellknownthatthefuzzyclusteringcanobtainarobust result as comparedwith conventionalhardclustering (Silviu 2013). Conventional clusteringmeansclassifyingthegivenobservationasexclusiveclusters.Itcanbeclearlyseenwhetheranobjectbe-longstoaclusterornot.However,suchapartitionisinsufficienttorepresentmanyrealsituations.There-fore,afuzzyclusteringmethodisofferedtoconstructclusterswithuncertainboundaries,sothismethodal-lowsthatoneobjectbelongstosomeoverlappingclus-terstosomedegree.Inotherswords,theessenceoffuzzyclusteringistoconsidernotonlythebelongingstatustoclusters,butalsotoconsidertowhatdegreetheobjectsbelongtotheclusters(Sato-Ilicetal.2006).Oneofthemainadvantagesoffuzzyclusteringistheabilitytoexpressambiguityinanassignmentofob-jectstoclusters(Silviu2013).Acorrespondingfuzzysetwasusedtodescribetheuncertainties(Hanetal.2011).However,apartfromthis,experimentalresultsprovethatfuzzyclusteringseemsalsotobemorero-bustintermsoflocalminimaoftheobjectivefunction(Klawonn2004).Anotherdistinctadvantageoffuzzyclusteringoveritscrispcounterpartisthatthecon-tinuousrangeofthecombinatorialfunctionsturnsintosmoothfunctions.Thismakesitpossibletodesignal-gorithmsthataremorelikelytoattainaglobalsolu-tion,whereascrisptechniquesoftenwindupinthelocalsolution.(Rousseeuw1995).Thefuzzyrelationbetween samples is quantified in fuzzy cluster, sofuzzycluster ismoreobjectiveandaccurate (Yang2011).Inrecentyears,thefuzzyclusteringhasbeenwide-

lystudiedandappliedinavarietyofkeyareas(WangandZhang2011)suchasindatamining,economicanalysis,andselectionevaluationindices(Xuetal.2005).Lietal.(2008)usedthismethodtoselecttheevaluationindicesofstockinvestmentvalue,provid-inganempiricalbasisforartificialintelligencemeth-odsinthestockvalueofinvestment.Guanetal.(2009)appliedthefuzzyclusteringapproachinconstructingtheevaluation indexsystemofcorecompetenceof

Selecting Evaluation Indices for Cleaner Production of Plantation Logging in Southern China ... (71–87) A. Yu et al.

Croat. j. for. eng. 37(2016)1 75

corporationandachievedverygoodresults.Yanetal.(2008)forecastedtheheavyrainstormbasedonthefuzzyclustertypeinJiangsuprovinceandreducedthestormemptyreportedrates.Chibaetal.(2012)ana-lyzedthewebsurveydatawiththesimilarityfuzzyclusterandshowedabetterperformancebyusingnu-mericalexamples.Asecondaryselectionshouldbeusedbythefuzzy

clustermethod.Thebasicideaoffuzzyclusterwastoconstructthefuzzymatrixaccordingtoattributesofaresearchobject,andonthisbasistheclusteringrela-tionwasdeterminedaccordingtocertainsubordinaterelations (Peng 2003).

Theprocess of the fuzzy clustermethod is de-scribedbythefollowing3steps:1)Setupafuzzysimilaritymatrixbycalculatingsimilarcoefficientsbetweensamplesandvari-ables.

2)Transform the fuzzy similaritymatrix into afuzzyequivalencematrixwiththehelpoffuzzyoperation.

3)Classifythefuzzyequivalencematrixaccordingtoadifferentfuzzygraphλ.

3.3 Data processingThefuzzyclusterprocessbeginsbysettingnitems

asaclassification,theindicatorsetX = {X1,X2,...,Xn},withavailablem-dimensionalvectordescribingthesample,Xi = {X1i,X2i,...,Xmi},i=1,2,...,n.AsthereweresomequalitativeanalysisindicesinCP evaluation of plantationharvesting,thispaperusedafivegradeLik-ertscaletoevaluateindices,rangingfrom»veryim-portant(5)«to»notcare(1)«,todetermineabettermeasureofeachindex.Themembershipfunctionwasthendefined:twas

thenumberofclassificationsofcertainproperties,Cp for pclass,xwasanattributevalueofCp,u (x) = N (Cp) m,p=1,2,...,t. N (Cp)wasthenumberofattributeval-ues included in the class Cp.Followingtheabovepro-cess,datamatrixwasinitialized,ifyijrepresentsthepropertyvalueoftheithrowandcolumnj,then0≤yij≤1,and yijsizereflectsthedependenceofthepropertyvaluefortheproperty.Establishingthefuzzysimilarmatrix:Thedomain

U = {y1,y2,...,yn}wasconcerned,yi,yjrelationshipwasdescribedbyR (yi,yj).Thereweremanymethodstohelpsetupafuzzysimilaritymatrix,suchasthedis-tancemethod, correlation coefficientmethod, andmaximumandminimummethod.Boththemaximumandminimummethod and correlation coefficientmethodwereusedinthispapertosetupafuzzysim-ilaritymatrixfortheCPevaluationofplantationlog-ging, and also to compare the difference betweenthem.

(1) Maximum and minimum methodAvalueiscalculatedbytheeq.(1):

( ) ( )( )

m

ik jki , j k 1m

ik jkk 1

1,

min , ,

max ,

i j

y yR y y i j

y y=

=

= = ≠

∑∑

(1)

Where,yikwastheattributevalueofrowicolumnk;yjkwastheattributevalueofrowjcolumnk.

Table 1 CP evaluation indicators system for forest plantation loggi

Prim

ary

index

sys

tem

for c

p ev

aluat

ion

of p

lanta

tion

logg

ing

First level index Second level index

Cutting area design

Cutting area division (x1)

Cutting area survey (x2)

Engineering design (x3)

Production process design (x4)

Logging technology

Rationality of operation process (x5)

Advanced of operation technology (x6)

Efficiency (x7)

Human-machine-environment harmony (x8)

Economics and safety of ways to work (x9)

Impacts on ecological environment

Soil physical properties (x10)

Soil chemical properties (x11)

Soil and water conservation (x12)

Injury rate of retention tree in slash (x13)

Average wind speed and temperature (x14)

Biomass (x15)

Biodiversity (x16)

The rate of slash soil erosion area (x17)

Resources and energy use

The number of discarded wood in cutting area (x18)

Utilization rate of wood (x19)

Utilization rate of slash (x20)

The number of discarded wood in the landing place (x21)

Logging equipment fuel consumption (x22)

Sustainable development

Survival ratio of renew (x23)

Renew ratio of cutting area (x24)

Wood renewal utilization (x25)

Improvement of safety and management

Safety management (x26)

Equipment safety (x27)

Labor protection (x28)

Labor intensity (x29)

A. Yu et al. Selecting Evaluation Indices for Cleaner Production of Plantation Logging in Southern China ... (71–87)

76 Croat. j. for. eng. 37(2016)1

AfuzzysimilaritymatrixRwassetupasfollows:

( ) ( ) ( )( ) ( ) ( )

( ) ( ) ( )

1 1 1 2 1 n

2 1 2 2 2 n

n 1 n 2 n n

, , ,, , ,

, , ,

R y y R y y R y yR R y y R y y R y y

R y y R y y R y y

… = …

(2)

Asshownintheabovematrix,reflexivityandsym-metryaresatisfiedduetoR(yi，yi)=1;R(yi，yj)=R(yj，yi),butdonotmeetthetransitivity.Therefore,thevaluescannotbeclassifieddirectly.Squaresmethodwasusedtocalculatetransitive

closureofthefuzzymatrix,sothatafuzzyequivalencematrixwassetupfromthefuzzysimilaritymatrixR (asshownbelow).

2 4 2kR R R R→ → → → (3)

RkwasthetransitiveclosureofthefuzzymatrixwhenRk0Rk= R2k.Inotherwords,Rkwasthefuzzyequivalencematrix.Thecubeoperationwascalculatedasfollows:

( )k 10ij ik jkm

A R R A R R=

= ↔ ∧= ∨ (4)

λwasthefuzzygraph：

( ) ( )ij ij n nn n0,1 ( )R r R r ××

= ∀ = ll l∈ (5)where:

( ) ijij

ij

1,0,

rr

rl

ll

≥= <,soRλwasthefuzzygraphofmatrixRo.

Differentvalueswouldbeassignedtoλfromlargetosmallafterthefuzzyequivalencematrixwassetup,anddifferentclassificationswouldbegainedbycalcu-lating l.Inotherwords,lwasassignedbytheactualneeds,andclassificationwasselectedbyl(Lietal.2003).Arepresentativeindexwasselectedfromeachclas-

sificationas the typical indexafterclassifying.Thespecificmethodwasthefollowing:first,correlationcoefficientsofeachclassificationwerecalculated;then,theaveragesofthesquaresofthecorrelationcoeffi-cientbetweenoneindexandtheotherwerecalculated,andthemaximumwasthetypicalindex.Theindexcouldbeputintotheindexset,ifonlyoneindexwasclassifiedandoneindexoftwoindicesexistedinclas-sification(SârbuandEinax2008).ThemainfactorsthatimpactedtheCPofplanta-

tionloggingwouldbetheindexofclusteronthebasisofliteraturereviewandinvestigations.Wedesignedthe questionnaire according to the content and fea-turesofcleanerproductioninplantationlogging,is-suedover100questionnairestoalmosttwentyfor-

estrycompaniesoruniversitiesbyemail,includingcollegesofforestry,forestryresearchinstitutes,forestengineeringenterpriseandsoon,andrecovered30validquestionnaires.AfivegradeLikert scalewasusedtoevaluateindices.AllthirtysampleswereusedfortheanalysisandtherawdataisshowninTable2.Themembershipfunctionwascalculatedfromthe

definitionitself,andaninitializationprocesswasusedfor these data. Accordingtotherawdata,membershipfunctionofeachattributeiscalculatedandshowninTable3.Inthefirstattribute,x1 meansthefirstindex(cuttingareadivision);{1–5}meanstheimportantde-gree(from»veryimportant{5}«to»notcare{1}«);0.37,0.40,0.23weretheproportionofrating{4},{5}and{3}in30samples,respectively.Aftermappingeachmem-bershipfunction,theresultinginitializeddataispre-sentedinTable4.Accordingtotheeq.(1)andcombiningtheinitial-

izeddata,fuzzysimilarmatricesRwereestablished.Matricesofcuttingareadesign(6),loggingtechnology(7),impactsonecologicalenvironment(8),resourcesandenergyuse(9),sustainabledevelopmentandsafe-typroduction(10),andlaborprotection(11)werecal-culatedwiththemaximumandminimummethod,asshownineq.(6)–(11).Inthesesimilarmatrices,eachvaluemeansthecorrelationoftwoindices;thehighervaluehasthestrongercorrelation,thusvalue1meansfullycorrelated.Forexample,inmatrix(6),thefirstrow,thevalues1,0.6693,0.8085,0.7380meanthecor-relationbetweenindexofthefirstandfirst,thefirstandthesecond,thefirstandthethird,thefirstandthefourth, respectively. In thefirst column, thevaluesmeaningasthefirstrow,andsoon.

1.0000 0.6693 0.8085 0.73800.6693 1.0000 0.6904 0.65440.8085 0.6904 1.0000 0.67910.7380 0.6544 0.6791 1.0000

(6)

1.0000 0.7408 0.6813 0.5171 0.64410.7408 1.0000 0.6429 0.6699 0.61030.6813 0.6429 1.0000 0.5211 0.52030.5171 0.6699 0.5211 1.0000 0.54130.6441 0.6103 0.5203 0.5413 1.0000

(7)

1.00000.51250.62850.52270.64660.66670.72930.60330.51251.00000.63840.55860.54720.52060.51450.52690.62850.63841.00000.65220.62090.68310.64860.66030.52270.55860.65221.00000.52830.55600.54430.57310.64660.54720.62090.52831.00000.70610.68790.61770.66670.52060.68310.55600.70611.00000.72210.67310.72930.51450.64860.54430.68790.72211.00000.65220.60330.52690.66030.57310.61770.67310.65221.0000

(8)

Selecting Evaluation Indices for Cleaner Production of Plantation Logging in Southern China ... (71–87) A. Yu et al.

Croat. j. for. eng. 37(2016)1 77

Tabl

e 2

Raw

dat

a fro

m th

e qu

estio

nnair

e

Inde

xR 1

R 2R 3

R 4R 5

R 6R 7

R 8R 9

R 10

R 11

R 12

R 13

R 14

R 15

R 16

R 17

R 18

R 19

R 20

R 21

R 22

R 23

R 24

R 25

R 26

R 27

R 28

R 29

R 30

X 14

45

44

53

55

43

53

54

55

53

44

55

54

34

33

4

X 22

33

44

34

34

43

22

33

11

52

34

45

53

32

34

3

X 33

33

45

55

35

54

43

54

43

45

44

55

54

43

44

5

X 42

44

24

43

43

42

24

22

24

44

34

55

53

33

25

3

X 55

33

45

34

54

44

55

54

45

55

54

55

54

44

44

5

X 64

55

34

34

33

44

33

45

45

54

34

35

43

54

35

3

X 75

35

44

54

53

45

43

45

45

34

43

24

34

44

44

4

X 82

54

35

35

33

42

31

33

21

54

53

45

52

32

24

3

X 93

23

34

55

43

35

53

23

33

42

43

34

34

33

25

3

X 10

44

45

43

24

31

24

41

33

23

24

44

55

33

22

34

X 11

44

35

44

45

44

45

43

55

55

43

35

34

44

44

44

X 12

45

53

43

44

43

45

53

43

44

44

35

55

43

33

43

X 13

42

43

13

53

13

34

44

33

23

34

32

53

22

23

33

X 14

53

24

41

35

23

24

23

34

35

45

12

54

22

22

22

X 15

54

33

41

44

34

44

33

32

23

33

52

55

43

22

32

X 16

33

41

45

54

24

23

23

24

31

43

24

55

22

32

43

X 17

41

14

31

41

23

41

33

35

41

31

34

43

33

23

52

X 18

54

45

55

54

45

34

53

54

43

35

33

44

34

44

43

X 19

54

43

55

44

55

45

43

45

35

55

33

44

34

44

54

X 20

54

44

33

51

23

44

34

34

24

45

23

44

33

22

44

X 21

53

55

43

43

45

43

55

43

34

35

33

44

43

44

54

X 22

24

44

44

54

33

43

25

35

52

45

13

54

22

22

42

X 23

45

55

55

53

34

53

54

43

54

43

12

54

44

43

53

X 24

22

22

42

41

21

23

51

21

23

44

32

55

32

22

42

X 25

32

44

44

53

13

14

43

33

25

24

32

55

32

22

42

X 26

45

54

53

45

45

34

44

45

35

55

32

55

33

33

32

X 27

54

44

45

54

35

54

44

54

35

34

23

44

44

44

43

X 28

42

41

32

32

15

44

14

43

32

44

33

43

44

43

44

X 29

52

43

32

33

32

45

42

53

44

24

33

34

33

23

33

A. Yu et al. Selecting Evaluation Indices for Cleaner Production of Plantation Logging in Southern China ... (71–87)

78 Croat. j. for. eng. 37(2016)1

Table 3 Membership function of each attribute

( ){ }{ }{ }

1

1 1

1

0.37 40.40 50.23 3

xu x x

x

… ∈= … ∈ … ∈

( )

{ }{ }{ }{ }{ }

2

2

2 2

2

2

0.07 10.17 20.40 30.27 40.10 5

xx

u x xxx

… ∈

… ∈= … ∈ … ∈ … ∈

( ){ }{ }{ }

3

3 3

3

0.23 30.40 40.37 5

xu x x

x

… ∈= … ∈ … ∈

( ){ }{ }{ }{ }

4

44

4

4

0.27 20.23 30.37 40.13 5

xx

u xxx

… ∈

… ∈= … ∈ … ∈

( ){ }{ }{ }

5

5 5

5

0.10 30.43 40.47 5

xu x x

x

… ∈= … ∈ … ∈

( ){ }{ }{ }

6

6 6

6

0.37 30.37 40.27 5

xu x x

x

… ∈= … ∈ … ∈

( ){ }{ }{ }{ }

7

77

7

7

0.03 20.20 30.53 40.23 5

xx

u xxx

… ∈

… ∈= … ∈ … ∈

( )

{ }{ }{ }{ }{ }

8

8

8 8

8

8

0.07 10.20 20.33 30.17 40.23 5

xx

u x xxx

… ∈

… ∈= … ∈ … ∈ … ∈

( ){ }{ }{ }{ }

9

99

9

9

0.13 20.50 30.20 40.17 5

xx

u xxx

… ∈

… ∈= … ∈ … ∈

( )

{ }{ }{ }{ }{ }

10

10

10 10

10

10

0.07 10.20 20.27 30.37 40.10 5

xx

u x xxx

… ∈

… ∈= … ∈ … ∈ … ∈

( ){ }{ }{ }

11

11 11

11

0.17 30.57 40.26 5

xu x x

x

… ∈= … ∈ … ∈

( ){ }{ }{ }

12

12 12

12

0.33 30.43 40.24 5

xu x x

x

… ∈= … ∈ … ∈

( ){ }{ }{ }

13

13 13

13

0.07 2,50.20 2,40.47 3

xu x x

x

… ∈= … ∈ … ∈

( )

{ }{ }{ }{ }{ }

15

15

15 15

15

15

0.03 10.20 20.37 30.27 40.13 5

xx

u x xxx

… ∈

… ∈= … ∈ … ∈ … ∈

( ){ }{ }{ }

16

16 16

16

0.07 10.27 2,3,40.13 5

xu x x

x

… ∈= … ∈ … ∈

( ){ }{ }{ }{ }

17

1717

17

17

0.23 1,40.10 20.37 30.07 5

xx

u xxx

… ∈

… ∈= … ∈ … ∈

( ){ }{ }{ }

18

18 18

18

0.27 30.43 40.30 5

xu x x

x

… ∈= … ∈ … ∈

( ){ }{ }{ }

19

19 19

19

0.20 30.43 40.27 5

xu x x

x

… ∈= … ∈ … ∈

( )

{ }{ }{ }{ }{ }

20

20

20 20

20

20

0.03 10.17 20.27 30.43 40.10 5

xx

u x xxx

… ∈

… ∈= … ∈ … ∈ … ∈

( ){ }{ }{ }

21

21 21

21

0.33 30.40 40.27 5

xu x x

x

… ∈= … ∈ … ∈

( )

{ }{ }{ }{ }{ }

22

22

22 22

22

22

0.03 10.27 20.17 30.33 40.20 5

xx

u x xxx

… ∈

… ∈= … ∈ … ∈ … ∈

( ){ }{ }{ }{ }

23

2323

23

23

0.03 1,20.23 30.33 40.37 5

xx

u xxx

… ∈

… ∈= … ∈ … ∈

( ){ }{ }{ }{ }

24

2424

24

24

0.13 1,30.47 20.17 40.10 5

xx

u xxx

… ∈

… ∈= … ∈ … ∈

( )

{ }{ }{ }{ }{ }

25

25

25 25

25

25

0.07 10.17 20.40 30.23 40.13 5

xx

u x xxx

… ∈

… ∈= … ∈ … ∈ … ∈

( ){ }{ }{ }{ }

26

2626

26

26

0.03 20.17 30.50 40.30 5

xx

u xxx

… ∈

… ∈= … ∈ … ∈

( ){ }{ }{ }

27

27 27

27

0.23 30.53 40.24 5

xu x x

x

… ∈= … ∈ … ∈

( )

{ }{ }{ }{ }{ }

28

28

28 28

28

28

0.10 10.17 20.40 30.30 40.03 5

xx

u x xxx

… ∈

… ∈= … ∈ … ∈ … ∈

( ){ }{ }{ }

29

29 29

29

0.20 20.33 3,40.14 5

xu x x

x

… ∈= … ∈ … ∈

Selecting Evaluation Indices for Cleaner Production of Plantation Logging in Southern China ... (71–87) A. Yu et al.

Croat. j. for. eng. 37(2016)1 79

Tabl

e 4

Initi

alize

d da

ta

Inde

xR 1

R 2R 3

R 4R 5

R 6R 7

R 8R 9

R 10

R 11

R 12

R 13

R 14

R 15

R 16

R 17

R 18

R 19

R 20

R 21

R 22

R 23

R 24

R 25

R 26

R 27

R 28

R 29

R 30

X 10.

370.

370.

400.

370.

370.

400.

230.

400.

400.

370.

230.

400.

230.

400.

370.

400.

400.

400.

230.

370.

370.

400.

400.

400.

370.

230.

370.

230.

230.

37

X 20.

170.

400.

400.

270.

270.

400.

270.

400.

270.

270.

400.

170.

170.

400.

400.

070.

070.

100.

170.

400.

270.

270.

100.

100.

400.

400.

170.

400.

270.

40

X 30.

230.

230.

230.

400.

370.

370.

370.

230.

370.

370.

400.

400.

230.

370.

400.

400.

230.

400.

370.

400.

400.

370.

370.

370.

400.

400.

230.

400.

400.

37

X 40.

270.

370.

370.

270.

370.

370.

230.

370.

230.

370.

270.

270.

370.

270.

270.

270.

370.

370.

370.

230.

370.

130.

130.

130.

230.

230.

230.

270.

130.

23

X 50.

470.

100.

100.

430.

470.

100.

430.

470.

430.

430.

430.

470.

470.

470.

430.

430.

470.

470.

470.

470.

430.

470.

470.

470.

430.

430.

430.

430.

430.

47

X 60.

370.

270.

270.

370.

370.

370.

370.

370.

370.

370.

370.

370.

370.

370.

270.

370.

270.

270.

370.

370.

370.

370.

270.

370.

370.

270.

370.

370.

270.

37

X 70.

230.

200.

230.

530.

530.

230.

530.

230.

200.

530.

230.

530.

200.

530.

230.

530.

230.

200.

530.

530.

200.

030.

530.

200.

530.

530.

530.

530.

530.

53

X 80.

200.

230.

170.

330.

230.

330.

230.

330.

330.

170.

200.

330.

070.

330.

330.

200.

070.

230.

170.

230.

330.

170.

230.

230.

200.

330.

200.

200.

170.

33

X 90.

500.

130.

500.

500.

200.

170.

170.

200.

500.

500.

170.

170.

500.

130.

500.

500.

500.

200.

130.

200.

500.

500.

200.

500.

200.

500.

500.

130.

170.

50

X 10

0.37

0.37

0.37

0.10

0.37

0.27

0.20

0.37

0.27

0.07

0.20

0.37

0.37

0.07

0.27

0.27

0.20

0.27

0.20

0.37

0.37

0.37

0.10

0.10

0.27

0.27

0.20

0.20

0.27

0.37

X 11

0.57

0.57

0.17

0.27

0.57

0.57

0.57

0.27

0.57

0.57

0.57

0.27

0.57

0.17

0.27

0.27

0.27

0.27

0.57

0.17

0.17

0.27

0.17

0.57

0.57

0.57

0.57

0.57

0.57

0.57

X 12

0.43

0.23

0.23

0.33

0.43

0.33

0.43

0.43

0.43

0.33

0.43

0.23

0.23

0.33

0.43

0.33

0.43

0.43

0.43

0.43

0.33

0.23

0.23

0.23

0.43

0.33

0.33

0.33

0.43

0.33

X 13

0.20

0.20

0.20

0.47

0.07

0.47

0.07

0.47

0.07

0.47

0.47

0.20

0.20

0.20

0.47

0.47

0.20

0.47

0.47

0.20

0.47

0.20

0.07

0.47

0.20

0.20

0.20

0.47

0.47

0.47

X 14

0.17

0.20

0.37

0.20

0.20

0.07

0.20

0.17

0.37

0.20

0.37

0.20

0.37

0.20

0.20

0.20

0.20

0.17

0.20

0.17

0.07

0.37

0.17

0.20

0.37

0.37

0.37

0.37

0.37

0.37

X 15

0.13

0.27

0.37

0.37

0.27

0.03

0.27

0.27

0.37

0.27

0.27

0.27

0.37

0.37

0.37

0.20

0.20

0.37

0.37

0.37

0.13

0.20

0.13

0.13

0.27

0.37

0.20

0.20

0.37

0.20

X 16

0.27

0.27

0.27

0.07

0.27

0.13

0.13

0.27

0.27

0.27

0.27

0.27

0.27

0.27

0.27

0.27

0.27

0.07

0.27

0.27

0.27

0.27

0.13

0.13

0.27

0.27

0.27

0.27

0.27

0.27

X 17

0.23

0.23

0.23

0.23

0.37

0.23

0.23

0.23

0.10

0.37

0.23

0.23

0.37

0.37

0.37

0.07

0.23

0.23

0.37

0.23

0.37

0.23

0.23

0.37

0.37

0.37

0.10

0.37

0.07

0.10

X 18

0.30

0.43

0.43

0.30

0.30

0.30

0.30

0.43

0.43

0.30

0.27

0.43

0.30

0.27

0.30

0.43

0.43

0.27

0.27

0.30

0.27

0.27

0.43

0.43

0.27

0.43

0.43

0.43

0.43

0.27

X 19

0.37

0.43

0.43

0.20

0.37

0.37

0.43

0.43

0.37

0.37

0.43

0.37

0.43

0.20

0.43

0.37

0.20

0.37

0.37

0.37

0.20

0.20

0.43

0.43

0.20

0.43

0.43

0.43

0.37

0.43

X 20

0.10

0.43

0.43

0.43

0.27

0.27

0.10

0.03

0.17

0.27

0.43

0.43

0.27

0.43

0.27

0.43

0.17

0.43

0.43

0.10

0.17

0.27

0.43

0.43

0.27

0.27

0.17

0.17

0.43

0.43

X 21

0.27

0.33

0.27

0.27

0.40

0.33

0.40

0.33

0.40

0.27

0.40

0.33

0.27

0.27

0.40

0.33

0.33

0.40

0.33

0.27

0.33

0.33

0.40

0.40

0.40

0.33

0.40

0.40

0.27

0.40

X 22

0.27

0.33

0.33

0.33

0.33

0.33

0.20

0.33

0.17

0.17

0.33

0.17

0.27

0.20

0.17

0.20

0.20

0.27

0.33

0.20

0.03

0.17

0.20

0.33

0.27

0.27

0.27

0.27

0.33

0.27

X 23

0.33

0.37

0.37

0.37

0.37

0.37

0.37

0.23

0.23

0.33

0.37

0.23

0.37

0.33

0.33

0.23

0.37

0.33

0.33

0.23

0.03

0.03

0.37

0.33

0.33

0.33

0.33

0.23

0.37

0.23

X 24

0.47

0.47

0.47

0.47

0.17

0.47

0.17

0.13

0.47

0.13

0.47

0.13

0.10

0.13

0.47

0.13

0.47

0.13

0.17

0.17

0.13

0.47

0.10

0.10

0.13

0.47

0.47

0.47

0.17

0.47

X 25

0.40

0.17

0.23

0.23

0.23

0.23

0.13

0.40

0.07

0.40

0.07

0.23

0.23

0.40

0.40

0.40

0.17

0.13

0.17

0.23

0.40

0.17

0.13

0.13

0.40

0.40

0.40

0.40

0.40

0.17

X 26

0.50

0.30

0.30

0.50

0.30

0.17

0.50

0.30

0.50

0.30

0.17

0.50

0.50

0.50

0.50

0.30

0.17

0.30

0.30

0.30

0.03

0.17

0.50

0.50

0.50

0.50

0.50

0.50

0.50

0.17

X 27

0.23

0.53

0.53

0.53

0.53

0.23

0.23

0.53

0.23

0.23

0.23

0.53

0.53

0.53

0.23

0.53

0.23

0.23

0.23

0.53

0.23

0.23

0.53

0.23

0.53

0.53

0.53

0.23

0.53

0.53

X 28

0.30

0.17

0.30

0.10

0.40

0.17

0.40

0.17

0.10

0.03

0.30

0.30

0.10

0.30

0.30

0.40

0.40

0.17

0.30

0.30

0.40

0.40

0.40

0.30

0.40

0.40

0.17

0.40

0.40

0.40

X 29

0.13

0.20

0.33

0.33

0.33

0.20

0.33

0.33

0.33

0.20

0.33

0.13

0.33

0.20

0.13

0.33

0.33

0.33

0.20

0.33

0.33

0.33

0.33

0.33

0.33

0.33

0.33

0.20

0.13

0.33

A. Yu et al. Selecting Evaluation Indices for Cleaner Production of Plantation Logging in Southern China ... (71–87)

80 Croat. j. for. eng. 37(2016)1

1.0000 0.8198 0.7030 0.8040 0.68760.8198 1.0000 0.6828 0.8082 0.66370.7030 0.6828 1.0000 0.6760 0.65530.8040 0.8082 0.6760 1.0000 0.70500.6876 0.6637 0.6553 0.7050 1.0000

(9)

1.0000 0.5541 0.60300.5541 1.0000 0.51310.6030 0.5131 1.0000

(10)

1.0000 0.6837 0.5846 0.58630.6837 1.0000 0.5798 0.60160.5846 0.5798 1.0000 0.66670.5863 0.6016 0.6667 1.0000

(11)

Asshownintheabovematrices6–10,reflexivityand symmetry are satisfied due to R(yi，yi)=1; R(yi，yj)=R(yj，yi), but do not meet the transitivity.Therefore, values cannot be classified directly. So,fuzzyequivalentmatriceswereestablishedaccordingtotheeq.(3).Sixfuzzyequivalentmatricesofcuttingareadesign(12),loggingtechnology(13),impactsonecologicalenvironment(14),resourcesandenergyuse(15),sustainabledevelopmentandsafetyproduction(16),andlaborprotection(17)shouldbecalculatedbythesquaresmethod,asshownineq.(12)–(17).Matrices(12)–(17),reflexivity,symmetryandtran-

sitivityareallsatisfied,soclassificationwillbedonedirectly.Eachvalueinthematricesmeansthel value.

1.0000 0.6904 0.8085 0.73800.6904 1.0000 0.6904 0.69040.8085 0.6904 1.0000 0.73800.7380 0.6904 0.7380 1.0000

(12)

1.0000 0.7408 0.6813 0.6699 0.64410.7408 1.0000 0.6813 0.6699 0.64410.6813 0.6813 1.0000 0.6699 0.64410.6699 0.6699 0.6699 1.0000 0.64410.6441 0.6441 0.6441 0.6441 1.0000

(13)

1.00000.63840.68310.65220.70610.72210.72930.67310.63841.00000.63840.63840.63840.63840.63840.63840.68310.63841.00000.65220.68310.68310.68310.67310.65220.63840.65221.00000.65220.65220.65220.65220.70610.63840.68310.65221.00000.70610.70610.67310.72210.63840.68310.65220.70611.00000.72210.67310.72930.63840.68310.65220.70610.72211.00000.67310.67310.63840.67310.65220.67310.67310.67311.0000

(14)

1.0000 0.8198 0.7030 0.8082 0.70500.8198 1.0000 0.7030 0.8082 0.70500.7030 0.7030 1.0000 0.7030 0.70300.8082 0.8082 0.7030 1.0000 0.70500.7050 0.7050 0.7030 0.7050 1.0000

(15)

1.0000 0.5541 0.60300.5541 1.0000 0.55410.6030 0.5541 1.0000

(16)

1.0000 0.6837 0.6016 0.60160.6837 1.0000 0.6016 0.60160.6016 0.6016 1.0000 0.66670.6016 0.6016 0.6667 1.0000

(17)

Accordingtotheeq.(4)and(5),λcutmatriceswerecalculatedanddifferentclassificationsweregained.Sixclassifiedresultsofcuttingareadesign(Table5),loggingtechnology(Table6),impactsonecologicalenvironment(Table7),resourcesandenergyuse(Ta-ble8),sustainabledevelopmentandsafetyproduction(Table9),andlaborprotectionindices(Table10)canbecalculatedbyassigningtoλfromlargetosmallandclassification,asshowninTables5–10.Atotaloftwelveindiceswerechosenforevalua-

tion.Twoindiceswereselectedfromeachofthefol-lowingconditions:cuttingareadesign,loggingtech-

Table 5 The cluster result of cutting area design

l value Classification number Specific category

1 4 {X1},{X2},{X3},{X4}

0.81 3 {X1,X3},{X2},{X4}

0.74 2 {X1,X3,X4},{X2}

0.69 1 {X1,X2,X3,X4}

Table 6 The cluster result of logging technology

l value Classification number Specific category

1 5 {X5},{X6],{X7},{X8},{X9}

0.74 4 {X5,X6},{X7},{X8},{X9}

0.68 3 {X5,X6,X7},{X8},{X9}

0.67 2 {X5,X6,X7,X8},{X9}

0.64 1 {X5,X6,X7,X8,X9}

Selecting Evaluation Indices for Cleaner Production of Plantation Logging in Southern China ... (71–87) A. Yu et al.

Croat. j. for. eng. 37(2016)1 81

value of l=0.74,where{X2}wasapartdirectlyputintheindexset,butonetypicalindexshouldbeselectedfrom{X1，X3，X4}.Forloggingtechnology,specificcat-egories of {X5，X6，X7，X8} and {X9} yielded a value of l=0.67,where{X9}wasapartdirectlyputintheindexset,butonetypicalindexshouldbeselectedfrom{X5,

X6, X7, X8},similartotheothers.Similarindiceshavetoselectedbythecorrelationindexmethod.Here,theloggingtechnologyistakenasanexample.Thecorrelationindices r of X5，X6，X7，X8 should

becalculatedfirst,asshowninTable11.

Table 11 Correlation coefficients of X5, X6, X7, X8

rij X5 X5 X5 X5

X5 1.0000 0.2999 0.2723 0.0539

X6 0.2999 1.0000 0.1531 0.1322

X7 0.2723 0.1531 1.0000 0.1087

X8 0.0539 0.1322 0.1087 1.0000

ThecorrelationindicesR arecalculatedasfollows.

2 2 256 57 58

5 0.05573

r r rR

+ += = (18)

2 2 265 67 86

6 0.04363

r r rR

+ += = (19)

2 2 275 76 78

7 0.06843

r r rR

+ += = (20)

2 2 285 86 87

8 0.01073

r r rR

+ += = (21)

Inthisinstance,theresultsindicatethatR5>R6>R7>R8. Therefore, R5wasputintothecategorybecauseitwasthemaximum.Theresultsoftheabovecalculationsshowedthat

theindicesofloggingtechnologyweretherationalprocessesandeconomicsandsafewaystowork.So,theindicesofcuttingareadesign,impactsonecologi-calenvironment,environmentalbenefits,aswellassustainabledevelopmentandlaborprotectioncouldbecalculatedbytheabovemethods,andtheresultsareshowninTable12.TheindicesshowninTable12yieldedthefollow-

ingresults:first,therelativefuzzysimilaritymatrixwassetupbythemaximumandminimummethod;then, the fuzzy equivalencematrixwas calculatedfromsquaresandtransitiveclosure;finally,theindiceswereselectedbythecorrelationcoefficientmethod.

Table 7 The cluster result of ecological environmental impact

l value

Classification number

Specific category

1 8 {X10} {X11},{X12}.{X13},{X14},{X15},{X16},{X17}

0.73 7 {X10,X16} {X11},{X12}.{X13},{X14},{X15},{X17}

0.72 6 {X10,X15,X16},{X11},{X12}.{X13},{X14},{X17}

0.71 5 {X10,X14,X15,X16},{X11},{X12}.{X13},{X17}

0.68 4 {X10,X12,X14,X15,X16},{X11},{X13},{X17}

0.67 3 {X10,X12,X14,X15,X16,X17},{X11},{X13}

0.65 2 {X10,X12,X13,X14,X15,X16,X17},{X11},

0.64 1 {X10,X12,X13,X14,X15,X16,X17,X11},

Table 8 The cluster result of utilization of resources and energy

l value Classification number Specific category

1 5 {X18},{X19},{X20},{X21},{X22}

0.82 4 {X18,X19},{X20},{X21},{X22}

0.81 3 {X18,X19,X21},{X20},{X22}

0.71 2 {X18,X19,X21,X22},{X20}

0.7 1 {X18,X19,X21,X20,X22}

Table 9 The cluster result of sustainable development

l value Classification number Specific category

1 3 {X23},{X24},{X25}

0.6 2 {X23,X25},{X24}

0.5 1 {X23,X25,X24}

Table 10 The cluster result of safety production management and protection

l value Classification number Specific category

1 4 {X26},{X27},{X28},{X29}

0.68 3 {X26,X27},{X28},{X29}

0.67 2 {X26,X27},{X28,X29}

0.6 1 {X26,X27,X28,X29}

nology,impactsonecologicalenvironment,resourcesandenergyuse,sustainabledevelopmentandsafetyproduction,andlaborprotection.Forthecuttingarea,specificcategoriesof {X1，X3，X4} and {X2} yielded a

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82 Croat. j. for. eng. 37(2016)1

(2) Relation coefficient methodAfuzzysimilaritymatrixwassetupbytherelation

coefficientmethod,andthentheindicesofCP evalu-ationforplantationloggingcanbecalculatedbythestepsthatweresimilartothemaximumandminimummethod.Aftertherawdatawasinitialized,therelationcoef-

ficientsbetweeneachindexwerecalculated,andtheabsolutevalueoftherelationcoefficientscanbetheelementsfordeterminingthefuzzysimilaritymatrix.Sixfuzzysimilaritymatricesofcuttingareadesign(22),loggingtechnology(23),impactsontheecologicalenvironment(24),resourcesandenergyuse(25),sus-tainabledevelopmentandsafetyproductionmanage-ment(26)andlaborprotection(27)werecalculatedbyrelationcoefficientmethod,asshownineq.(22)–(27).

1.0000 0.1606 0.1473 0.05740.1606 1.0000 0.1168 0.08520.1473 0.1168 1.0000 0.37240.0574 0.0852 0.3724 1.0000

(22)

1.0000 0.2999 0.2723 0.0539 0.10840.2999 1.0000 0.1531 0.1322 0.00670.2723 0.1531 1.0000 0.1087 0.29410.0539 0.1322 0.1087 1.0000 0.07450.1084 0.0067 0.2941 0.0745 1.0000

(23)

1.00000.04600.00250.16570.09030.01860.42630.18350.04601.00000.16770.02140.37870.10730.10530.03100.00250.16771.00000.11790.09160.24810.08520.07480.16570.02140.11791.00000.17410.09760.14010.02970.09030.37870.09160.17411.00000.33940.39370.19630.01860.10730.24810.09760.33941.00000.15460.08690.42630.10530.08520.14010.39370.15461.00000.03590.18350.03100.07480.02970.19630.08690.03591.0000

(24)

1.0000 0.3713 0.0046 0.0516 0.13450.3713 1.0000 0.0218 0.2802 0.37440.0046 0.0218 1.0000 0.0237 0.29170.0516 0.2802 0.0237 1.0000 0.00760.1345 0.3744 0.2917 0.0076 1.0000

(25)

1.0000 0.0346 0.14120.0346 1.0000 0.10190.1412 0.1019 1.0000

(26)

1.0000 0.2620 0.1077 0.25880.2620 1.0000 0.0470 0.1584 (27)

Sixfuzzyequivalencematricesofcuttingareade-sign(28),loggingtechnology(29),impactsontheeco-logicalenvironment(30),resourcesandenergyuse(31),sustainabledevelopmentandsafetyproductionmanagement(32)andlaborprotection(33)werecal-culatedbythesquaresmethod,asshownineq.(28)–(33).

1.0000 0.1606 0.1473 0.14730.1606 1.0000 0473 0.14730.1473 0.1473 1.0000 0.37240.1473 0.1473 0.3724 1.0000

(28)

1.0000 0.2999 0.2723 0.0539 0.10840.2999 1.0000 0.1531 0.1322 0.00670.2723 0.1531 1.0000 0.1087 0.29410.0539 0.1322 0.1087 1.0000 0.07450.1084 0.0067 0.2941 0.0745 1.0000

(29)

Table 12 CP assessment indicators of plantation logging – six first grade indices and twelve second grade indices (max and min matrix method)

Cutting area design Logging technologyImpacts on ecological

environmentResources and

energy useSustainable

developmentSafety production management

and protection

Cutting area survey Rational processesSoil physical properties

Utilization ratio of wood

Survive ratio of renew Safety management

Engineering designEconomics and safety

of ways to workBiodiversity

Utilization ratio of slashes

Renew ratio of cutting area

Labor protection

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Croat. j. for. eng. 37(2016)1 83

1.0000 0.37870.24810.17410.39370.33940.42630.19630.3787 1.00000.24810.17410.37870.33940.37870.19630.2481 0.24811.00000.17410.24810.24810.24810.19630.1741 0.17410.17411.00000.17410.17410.17410.17410.3937 0.37870.24810.17411.00000.33940.39370.19630.3394 0.33940.24810.17410.33941.00000.33940.19630.4263 0.37870.24810.17410.39370.33941.00000.19630.1963 0.19630.19630.17410.19630.19630.19631.0000

(30)

1.0000 0.3713 0.2917 0.2802 0.37130.3713 1.0000 0.2917 0.2802 0.37440.2917 0.2917 1.0000 0.2802 0.29170.2802 0.2802 0.2802 1.0000 0.28020.3713 0.3744 0.2917 0.2802 1.0000

. (31)

1.0000 0.1019 0.14120.1019 1.0000 0.10190.1412 0.1019 1.0000

(32)

1.0000 0.2620 0.1077 0.25880.2620 1.0000 0.1077 0.25880.1077 0.1077 1.0000 0.10770.2588 0.2588 0.1077 1.0000

(33)

Laterstepswerequitethesameusingthemaxi-mum andminimummethod, and the indices areshowninTable13.ResultsfromTable12andTable13werequitesim-

ilar.Onlytwoindicesweredifferent,whichindicatesthatbothofthemethodswerereliableforcalculatingtheindex.Usingbothmethodsstrengthenstheanaly-sis.

4. DiscussionInthisstudy,wehaveselectedsomeevaluation

indices of CPonthebasisofplantationloggingandsetprinciples.CPhasbeenwidelyappliedinallkindsofindustry,butseldomusedinforestry.Inrecentyears,thetheoriesandconceptsofCPhavebeenconsideredfortheharvestingareainChina,buttheyonlydis-cussedtheconcept,roleoftarget,andnorealanalysisof theproducts.While theproductionprocesswasgenerallyfoundtobeenvironmentallyacceptabledur-ingtimberharvesting,amoreformalprocessisneed-edforanaccurateevaluation(Qiang2000,Zhao2000,Zhao2008,Yu2009).Therewasalackofspecificsandtargeted results inpractice, andguidancewasnotstrong in the forestenterprise.Thefindingsof this

studyindicateimplementationofcleanerproductionin China could have a guiding role in forest engineer-ingcompanies.Toevaluatethecontentsofcleanerproductionin

plantationharvestingoperations,wedistributed100questionnairestoprofessorsinuniversity,researchersinforestryresearchinstituteandloggersorworkersinforestryenterprisesandrecoveredthirtyvalidques-tionnaires.Thelowparticipationmayindicatethatmostofthemputlessemphasisoncleanerproduction,especiallytheforestengineeringenterprisesinChina.Ithasbeenproposedthat theChinesegovernmentshouldincreasepublicityandeducationinthisarea.Likeotherindustries,implementationcouldincludethe introductionof incentivesorrelevant lawsandregulationstoensurethatmoreattentionispaidonthecleanerproductionintheforestryenterprises.Accordingtotheinvestigationresultsbasedonthe

thirtysubmittedresponses,thefuzzyclusteringmeth-odwasusedtoinitiallyscreentwenty-ninesecond-gradeindices.Sixfirst-gradeindicesandtwelvesec-ond-gradeindiceswereselectedasformalevaluationindices.Asweallknow,theothersecond-gradeindi-cesnotselectedarealsoimportant,buttoomanyin-diceswillbedifficulttoanalyzeinpracticeinforestcompanies.Accordingtotheprinciplesfordetermin-ingevaluationindices,theindexsystemforCP could notcoveralltheprocessesintheplantationlogging.Generally themostsimpleandfocused indicesareimplementedeffectively.Thepurposeofthequestion-nairewasissuedfortheforestryenterprises,withthemoreimportantindicesrelatedtotheimplementationofcleanerproductioninplantationlogging.Accordingtothe30validquestionnaires,thefuzzyclustermeth-odswereusedtoselectthemoreimportantindices.Thisindicatesthattheselectedsecond-gradeindicesaremoreimportantthanothersecond-gradeindicesnot selected according to the results of questionnaires andfuzzyclustermethods.Atthesametime,severalmethodswereusedto

screenevaluationindices,suchasthegraycorrelationmethod,analytichierarchyprocess,etc.,(Shen2002,Xu2007)butthefuzzyclusteringanalysiswaswidelyusedforobjectivityandaccuracy(Yang2011).There-sultsshowedthatthefuzzyclusteringmethodisreli-ableforscreeningindices.CPofplantationlogginghaditsownadvantagescomparedwithotherCPob-jectivesthatwerecombined,suchassavingresources,reasonableuseofrenewableenergyinforests,protect-ingtheenvironmentinforestsandeducatingperson-alprotectionforworkers.ThebasicprinciplewithCP is»preventionmustcomefirst,treatmentshouldonly

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84 Croat. j. for. eng. 37(2016)1

beneededinspecialcircumstances«inallthestagesoftheloggingprocess.Ourinitialfindingsindicatethemethodsofusing

advanced technology and improving process andequipment.Differentloggingmethods(includedcut-ting,bucking,skiddingandtransportation)wereusedincuttingareasduetodifferentterrainconditions,andeventheworkingefficienciesdifferedwhenusingthesameloggingmethodsinthesamecuttingarea.Forexample,skiddingwithcablewaywassuitableforhillsormountaincommunities,butskiddingwithtractorswassuitableforflatcommunities.Theharvestingma-chinehasbeenusedduetoitshighworkefficiency;however,itisnotsuitableforallcuttingareasbecauseofworkingconditions.Therefore, it isbettertouseadvanced technologyand improveprocessingandequipmentbasedonlocalconditions.Secondly,inthewaysofsavingandrationallyus-

ingresourcesandenergy,thetreewastherawmate-rial for CPoflogging.Thebesttimetologwaswhenthe treebiomasshasbeenat itsmaximum.Ontheotherhand,thespecialcharacteristicsofCP for log-gingwerethecomplexworkingconditions,fertilityoftheslash,overlappingoftheworkingsystemandeco-logicalsystem,complexityandfuzzinessofmultiplefactors.Inrecentyears,twoareashavebeenstudiedon

plantationlogging.Oneareawastheimpactsoflog-gingontheecologicalenvironment,whicincludedthesoils,vegetation,treesurvival,wildanimals,biologicaldiversity, landscapes,anduseofslash(Wang2005,Rab1994aand1996b,Li1994,Qiu1998,Chen1999,Crokeetal.2001aand2006b,Blumfieldetal.2003,Hartantoetal.2003,Birdetal.2004,Penningtonetal.2004,Radeletal.2006,Demiretal.2007,Langeretal.2008,Freyetal.2009,Walmsleyetal.2009,Stoffeletal.2010)Theotherstudywasdoneontheecologicalloggingprocessesandtechnology,whichincludedtheevaluationofecological,economicandcombinedben-efits(Huang1995,Deng2005,Zhang2005,Spinelliet

al.2012,Berhongarayetal.2013).ManyevaluationsystemsforCPhavebeenwidelyusedinchemicalengineering, services,andagriculturesallover theworld.StudiesonCPforforestspointedoutthecon-ception,overallgoals,guidelines,andtheimplemen-tationofthemeasureswithoutfurtherinvestigations.InChina,somerulesandregulationsofCPhavebeenaccomplishedinafewlargeloggingenterprises,asindicatedinthearticle»TheMeasuresforCPbyGen-heForestryBureau«.Unfortunately,therewasnotanyfurtheranalysisinvolvingcontents,indexsystemforevaluation,andmethods forevaluation.Therefore,morestudieswillbeneededonCPforplantationlog-ging.

5. ConclusionsInthispaper,anindexsystemofCP evaluation for

plantationloggingwassetuponthebasisofCP,ac-cordingtothecharacteristicsofplantationlogging.Thecontentsofsuchanindexsystemincludedthefollowingsixfirst-gradecriteria:cuttingareadesign,loggingtechnology,impactsontheecologicalenviron-ment,resourcesandenergyuse,sustainabledevelop-mentandsafetyproductionmanagement,andlaborprotection.Thefuzzyclustermethodwasusedtose-lecttheindices.Finally,twelvesecond-gradeindiceswereselectedastheevaluationindices.Acomparisonusingbothmaximumandminimumanalysisandcor-relationanalysisshowedthat10ofthe12indiceswereacceptable.Thetwelvesecond-gradeindicesselectedarejustthefirststepforCP of logging. According to theresultsofselecting,thesemadethestandardforCP evaluationofplantationlogging.Then,accordingtothestandards,cleanerproductionauditwillbeimple-mentedtochecktheforestcompanies,expectingforestcompaniestomeetthestandards.Theimplementedguidelines of CPinplantationloggingwillgivethemtherightdirections.So,theresultsofselectingindiceswillbebeneficialforsustainableproductionandman-agementofplantationforestsinChina.

Table 13 CP assessment indicators of plantation logging – six first grade indices and twelve second grade indices (correlation coefficient matrix method)

Cutting area design

Logging technologyImpacts on the

ecological environmentResources and energy

useSustainable

developmentSafety production management

and labor protection

Cutting area survey

Rational processes Soil physical propertiesUtilization ratio of

woodSurvive ratio of

renewSafety management

Production process design

Economics and safety of ways to work

BiodiversityLogging equipment fuel

consumptionRenew ratio of

cutting areaLabor protection

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Croat. j. for. eng. 37(2016)1 85

AcknowledgmentsThisresearchreceivedsupportfromInternational

ScienceandTechnologyCooperationProjectsofChina(China–Finland)(2006DFA32840):StudyonHarvest-ingModelforPlantationForestBasedonIndustrialEcology.Theprojectwasfundedbythe»PriorityAca-demicProgramDevelopmentofJiangsuHigherEdu-cationInstitutions(PAPD)«.

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Received:October15,2014Accepted:April2,2015

Authors’address:

Assoc.prof.,AihuaYu,PhD.e-mail:azy0008@auburn.eduProf.,ChenZhao,PhD.e-mail:czh@njfu.edu.cnLecturer,YaoZhao,PhD.e-mail:zhaoyaonfu@163.comDepartmentofForestEngineeringNanjingForestryUniversity159RongPanRoad210037Nanjing,JiangsuprovinceP.R.CHINA

Assoc.prof.,TomGallagher,PhD.*e-mail:tgallagher@auburn.eduSchoolofForestryandWildlifeSciencesAuburnUniversity3425ForestryandWildlifeSciencesBuilding36830Auburn,AlabamaUSA

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