Risk Evaluation in Auto Spare Parts Transport Based on the

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1 MAEC Web of Cofeeces 100, Rsk Evaluato Auto Spae Pats aspot Based o the AHP Method Rog Zeg 1 ad Chag Xu 2 1 Wuha Huaxa Uvesty of echology, Wuha, Cha 2 Wuha Uvesty of echology, Wuha, Cha Abstact By way of example we aalyze vaous sks exst auto spae pats taspotato, buldg egeeg logstcs sk evaluato dex system of auto spae pats taspotato, ad the toducto of AHP, be moe atoal auto spae pats taspotato sk assessmet methods, stegthe sk maagemet auto spae pats auto spae pats taspotato to povde a efeece fo othe egeeg logstcs auto spae pats taspotato. 1 Itoducto Auto spae pats pmaly elates to taspot objects of taspot, hadlg, packagg ad stoage, these elatvely depedet but closely lked aspects costtute the complete logstcs pocess. I patcula, the pocess object taspotato sk s a objectve ealty, ad has a dyamc vaablty, dvesty, but also by subjectve factos, so the aalyss of egeeg logstcs sk s vey mpotat. [1]. Cuetly thee ae may eseach coceg logstcs sk[2-3], but ot a specfc sk assessmet system of auto spae pats taspotato. akg a hghway taspot pecast beams aj, fo example, the establshmet of a taspot sk facto assessmet model, a compehesve evaluato of the sk peseted fo the segmet pefabcated beams sk assessmet system ad sk cotol measues, to hedge agast the sk of auto spae pats taspotato auto spae pats sevces. 2 AHP Aalytc Heachy Pocess (Aalytc Heachy Pocess, AHP) s home Satty Ameca opeatos eseach the ealy 1970s to make hs decso aalyss method fo quattatve ad qualtatve. It polcymakes thought pocess complex decso-makg system wll be modeled quatfy. Applcato of ths method, the makes of complex poblems dow to a umbe of factos ad a umbe of levels, betwee the vaous factos pa wse compasos ad calculatos, get dffeet weghts, povde the bass fo selectg the best soluto[4-5]. AHP method ca be dvded to fou steps: Fst, aalyze the elatoshp betwee the vaous factos the system, ceate a system of heachcal stuctue; the the same level of mpotace of vaous elemets o a laye coespodg gudeles pa wse compaso, costuct pa wse compaso judgmet matx; ad the by the judgmet matx calculato s to compae elemets of the gudeles should be elatvely heavy weght; ad fally calculate the levels of the elemets of the oveall taget system combg weghts, ad sot. 3 he establshmet of auto spae pats taspotato sk assessmet model he Authos, publshed by EDP Sceces. hs s a ope access atcle dstbuted ude the tems of the Ceatve Commos Attbuto Lcese 4.0 (

2 MAEC Web of Cofeeces 100, Costucto of evaluato dex heachy Poject logstcs auto spae pats taspotato s a vey complex pocess, volvg may aeas of techology, maagemet, scece, etc., s also elated to the elevat factos affectg the taspot busess, maagemet secto, etc., fo the selected dcatos ae moe the actual pocess should emove duplcate factos avod lage devatos fom the actual stuato. aj hghway below a ceta pecast taspot fo example. 3.2 Judgmet matxt Afte the establshmet of the heachy aalyss model, the elatve mpotace of each facto o each scoe gve by expets. wo moe thgs to make a accuate compehesve judgmet, s assessed by expet opo, efeg to SUY e scale method, popoto to the scale defed by the extet of mpotace assged to costuct the dex levels of judgmet matx. o avod eos of judgmet, but also to costuct judgmet matx cosstecy test[6-7]. Judgmet matx calculato utlzg the elatve weght W ad each dex coeffcet matx chaactestc oot, as follows: matx; (1) calculate the matx poduct of all elemets each ow: (2) M be opeed the -th powe: W M ; M a, whee =1,2,...,, s the ode of the j j1 (3) 1, 2,..., W W W wll be omalzed: (4) Calculate the chaactestc oots: w max w j 1 1 w j BW ; W. Calculate the chaactestc oots level by a sgle sot cosstecy dex: max CI. ; 1. Radom Cosstecy Idex s the calculated: CR. CI ; f CR. 0.1that s acceptable cosstecy of judgmet RI. matx, whee the aveage adom cosstecy dex RI s deved usg a adom samplg method, the value show able 1. able 1. Aveage adom cosstecy dex R.I dmeso R.I Cteo level factos evomet, opeato, maagemet, auto spae pats vehcle to the taget laye U of total auto spae pats taspotato sk judgmet matx able 2-6. able 2. Judgemet matx of U-U U U 1 U 2 U 3 U 4 W 0 dex U 1 U 2 U 3 U 4 1 1/3 1/5 1/ / /2 1/ Pogamme laye facto U 1j of U 1 judgmet matx able 3. max =4.104 C.I=0.035 R.I=0.96 C.R=0.036<0.1 2

3 MAEC Web of Cofeeces 100, able 3. Judgemet matx of U 1 -U 1j U 1 U 11 U 12 U 13 W 1 dex U 11 U 12 U /3 1/ / max =3.04 C.I=0.02 R.I=0.58 C.R=0.03<0.1 able 4. Judgemet matx of U 2 -U 2j U 2 U 21 U 22 W dex U /3 U max =2 C.I=0 R.I=0 C.R=0<0.1 able 5. Judgemet matx of U 3 -U 3j U 3 U 31 U 32 U 33 W dex U 31 U 32 U /3 1/ / max =3.04 C.I=0.02 R.I=0.58 C.R=0.03<0.1 able 6. Judgemet matx of U 4 -U 4j U 4 U 41 U 42 U 42 W dex U 41 U /2 1/ max =3.013 C.I=0.007 U 43 1/ R.I= C.R=0.011<0.1 1 Whe = 2, C.R = 0 s exactly the same. CR lage the value, the wose the cosstecy of judgmet matx, the max matx due to the judgmet CR value s less tha 0.1, t s cosdeed that they have a satsfactoy cosstecy. It should be oted that pactce, the heachcal model of the umbe of layes of factos ad factos of pawse compasos betwee two values ae ot statc, but accodg to the specfc ccumstaces by expeeced, expet judgmet ad stog decso. 4 Fuzzy compehesve evaluato 4.1 Idetfy factos set ad evaluato set As the auto spae pats complex ealty, eve the expets ca ot gve a accuate assessmet ca oly be a vague assessmet. Lgustc vaables ca be appoxmated to descbe the complex pheomeo ot clealy defed chaactestcs. Such as "sk" as a facto set "hgh sk, hgh sk, modeate sk, geeal sk, low sk, o sk" ca be set as oe of ts judgmet. O pecast beam taspoted example, the judge set V = {a vey hgh sk, hgh sk, geeal sk, low sk, low sk}, ad quatfy. 3

4 MAEC Web of Cofeeces 100, able 7. Quatfed sk gade Rsk level Vey sk hgh Hgh sk Geeal sk Low sk Vey sk low Idcato Value (8,10) (6,8) (4,6) (2,4) (2,0) 4.2 Deteme the fuzzy elato matx ad membeshp Fuzzy Compehesve Evaluato of Mult-level system s to stat step by step to make a moe compehesve evaluato fom the lowest level up, get up to the hghest level of taget compehesve evaluato esults of the ogal poblem. Hee depatue fom the pogam level dcatos, the fst laye of each facto fuzzy compehesve evaluato ctea, ad the the taget laye fuzzy compehesve evaluato factos. (1) he secod level fuzzy compehesve evaluato facto. Ode membeshp R j j1, j2, j, the the secod level of sgle facto evaluato matx: R = B ˊ=W R = m m2 1 2 m 1, b 2,, b 3 facto to obta a secod level fuzzy compehesve evaluato level s b, whee s fuzzy Opeatos ca select the appopate algothm accodg to dffeet stuatos. Assessmet by the fst goup of 10 people o the secod level of each facto sgle facto evaluato factos, such as the factos set U 1 = {evomet, weathe, geology} thee factos of sk evaluato, assessmet team votg esults ae show able 8. U 11 evomet able 8. U 11 sk evaluato by expet Vey hgh sk Hgh sk Geeal sk Low sk Vey low sk U 12 Weathe U 13 geology Calculate the weght of each laye combg weghts he ght combato of computg the weght of each laye ae show able 9, ad cosstecy checkg. able 9. he total sot Computato sheet of U U U 11 U 12 U 13 U 21 U 22 U 1 U 2 U 3 U weght

5 MAEC Web of Cofeeces 100, U 31 U 32 U 33 U 41 U 42 U B CI. W ( CI. ) =(0.077,0.238,0.517,0.168)(0.02,0,0.02,0.007)= B RI. W ( RI. ) =(0.077,0.238,0.517,0.168)( 0.58,0,0.58,0.58)= B CR. W ( CR. ) =0.03<0.1,dcatg that meet the cofomace equemets. 4.4 Ealuato As ca be see fom able 7 that U 2 ad U 3 maage opeatoal mpact o auto spae pats taspotato safety pefabcated beams elatvely lage, ad elatvely small mpact o the evomet. U 33 level the secod stage secuty pesoel awaeess maxmum mpact o taspot. I the pocess of pecast auto spae pats taspotato to esue safe ad smooth t ca each the destato, the sk must be cotolled fom the maagemet ad opeato of two aspects, patcula, to stegthe the secuty pesoel educato. 5 Cocluso Step atcle usg AHP to aj, a hghway auto spae pats taspotato pecast beams, fo example, to buld a heachy of sk, combed wth expet opo to deteme the vaous levels of judgmet matx, ght by the fomula to calculate the factos of weght, ad cosstecy specto, fomg a total weght sot table, lad the foudato fo futhe evaluato of the sk of auto spae pats taspotato. Howeve, because data collecto s lmted, ths sk heachy eeds to be futhe mpoved. Ackowledgmets he authos thak the evewes who gave a though ad caeful eadg to the ogal mauscpt. he commets ae geatly appecated ad have help to mpove the qualty of ths pape. hs wok s suppoted pat by the Scetfc Reseach Pla of Hube Povce (No.B ). Refeeces 1. Wag, Alg. Fuzzy sk assessmet of costucto poject cotactos based o etopy-weght coeffcet method. Electc echology ad Cvl Egeeg (ICECE), 2011 Iteatoal Cofeece o IEEE, Makowsk A S, Maa M S. Fuzzy sk matx Joual of Hazadous Mateals, L, Chaoyag, C. Ye, ad Y. She. Rsk Assessmet of Subway Pt Costucto Based o Fuzzy Compehesve Evaluato. Chese Joual of Udegoud Space & Egeeg 10 (2014). 4. Ekut, Eha, ad A. Igolfsso. aspot Rsk Models fo Hazadous Mateals: Revsted. Socal Scece Electoc Publshg 5. ERKU Eha, ad INGOLFSSON Ama. aspot sk models fo hazadous mateals: evsted. Opeatos Reseach Lettes (2005). 5

6 MAEC Web of Cofeeces 100, Vema, Mash. Ralauto spae pats taspotatoato of dageous goods: A codtoal exposue appoach to mmze taspot sk. aspotato Reseach Pat C Emegg echologes 19 (2011). 7. Chapma, Rebekah L., et al. he mpact of school coectedess o volet behavo, taspot sk-takg behavo, ad assocated jues adolescece. Joual of School Psychology 49 (2011). 8. Paulo Ségo, Lucas Da Slva, E. D. A. Vaa, ad R. Maa Euce. Assessg outcome tehosptal fat taspot: the taspot sk dex of physologc stablty scoe at admsso. Ameca Joual of Peatology 29(2012) 6

Research of Education Evaluation Information Mining Technology Based on Gray Clustering Analysis and Fuzzy Evaluation Method

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