Fig. 1. Actual data. Fitting curve 发送量发展趋势. Passenger. people) (( x 2013) 7.773) (( x 1998) 12.5) (( x 2006) 2.102) (( x 2019) 27.

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1 211 Intrnational Confrnc on Computr and Softwar Modling IPCSIT vol.14 (211) (211) IACSIT Prss, Singapor Assssmnt Modl about th Impact of Shanghai Expo 21 on Transportation Economy Ran Hu 1,a, Xu Wang 2,b and Yachun Zhang 2,c + 1 Collg of Automation Enginring, Qingdao Univrsity, P.R of China, School of Economics, Qingdao Univrsity, P.R of China, Abstract. In this papr, w assss th 21 Expo s impact on th transportation conomy in Shanghai. W choos fiv diffrnt indicators about th transportation conomy and assum that th annual indx data bfor 24 wr not affctd by Expo. Thn, w adopt th fitting prdiction mthod, comparing prdictd indx with th actual data in tim sris. At th sam tim, w calculat th importanc wight of th diffrnt indicators in th transportation, thn furthr xplor th dirction of th industrial structur with industry analysis. Quantitativ analysis of th transportation conomy can b good rfrnc for China to organiz a similar big vnt in th futur in cas of th hug amount imput. Kywords: transportation conomy, impact assssmnt, fitting prdiction, importanc wight, quantitativ analysis 1. Introduction Th transportation conomy is a part of th third industry of a socity. Th proportion of trtiary industry is rlativly highr in cntral citis, such as Nw York and Tokyo. Th rason is that cntral citis hav rgional advantag, good infrastructur, convnint living conditions, abundant human rsourcs and a rlativly sound basis for th dvlopmnt and thus mor conduciv to dvlopmnt of th srvic functions of th trtiary industry. And to 21, Shanghai has only 6% of th shar. Shanghai should incras th proportion of trtiary industry in th futur to stimulat th conomy to a nw lvl. To mak prparation for Expo, Shanghai spd up th pac of urban dvlopmnt, such as construction of hub-typ, functionality, ntworks of urban infrastructur systms, xpansion of Pudong Intrnational Airport. During th Expo, th city's total rtail sals rachs 39.5 billion yuan, and occupancy rat of rooms rachs 78% on avrag in star hotl. In 21, 8,511,2 abroad tourists arrivd in Shanghai, which is 35.3% ovr th prvious yar. Shanghai should play ky rol in rgional conomy, focusing on th dvlopmnt of th third industry which is good for coordination of rgional dvlopmnt and ovrall planning. In this papr, w tak into account on part of th trtiary industry-transportation to analysis th impact of Shanghai Expo. Firstly, w choos fiv diffrnt indicators about th transportation conomy, using th fitting prdiction mthod to draw th lin curv and th smooth curv which stand for th actual data and th prdict data, rspctivly. Thn, w calculat th importanc wights of th two industris to gt th comprhnsiv xplanation of Expo impact. W assum that th rlativ construction of Expo mainly occurrd in 24-29, th Expo will bring tourism bnfits mainly in th last four yars, and th collction of data is objctiv with no subjctiv ffct on th modl analysis. 2. Assssmnt Modl of impact on Transportation Economy Dvlopmnt + a huran1121@163.com; b wangxu58@163.com; c mlodyrunrun@gmail.com 37

2 In th transport systm, w mainly us th indicators of railways, highways, volum of air fright, RPK(passngr turnovr) and cargohandling capacity, turnovr volum of goods to rflct th dvlopmnt of transportation. Passngr volum rflcts th quantity promotion of conomy and popl's livs accounting to transportation, and turnovr volum can rflct th ovrall rsults producd by th transport industry. Thy ar important indicators to study scal and spd of transport dvlopmnt. W slctd th fiv transportation indxs as follows: (Not: including railways, highways, ports, civil aviation) passngr volum (unit: million popl), passngr turnovr (unit: million popl km), cargo volum ( Unit: million tons), cargo turnovr (unit: million tons km), total port cargo throughput (unit: million tons). 2.1 Passngr Volum W collct th data bfor 24. W assum that th data ar not affctd by Expo. W us th curv fitting toolbox cftool in Matlab softwar, using a singl variabl curv approximation mthod to draw all transportation valuation trnds. This fitting mthod can prdict th possibl quantity of passngr volum in th nxt fw yars if w do not tak into account Expo factor. Thn w us th diffrnc btwn th prdictd data and th actual data to divid th prdictd data, and th avrag of th calculation rsults rflct th impact of Expo, which w us I to xprss. Drawing a lin graph about passngr volum and tim, w assum that th rlationship of two variabls is: y1 = a1 + a2 W do th curv fitting in th tool of cftool in Matlab, and gt th rasonabl fitting rsults. Th fitting function is providd blow, with R=.9762: (( x 213) 7.773) (( x ) 12.5) y1 = W import data into xcl tabl to draw two curvs. Th lin curv rprsnts th actual statistics of th indicator data, and th smooth curv rprsnts data prdictd by fitting function undr no influnc of Expo 旅客发送量统计值 无世博因素影响的旅客 Fitting curv 发送量发展趋势 Passngr 旅客发送量 Volum (Millon ( 万人次 ) popl) Fig. 1 W can quantiz th impact of Expo by th actual statistics and forcast valu. W dfin valu of impact as actual statistics minus forcast valu, and rat of impact as valu of impact dividd by th forcast valu. Finally, w calculatd th avrag impact rat of fiv yars from 25 to 29 as th comprhnsiv impact of Expo. Aftr statistics calculating, th valu of th Expo impact on passngr volum is I = RPK (passngr turnovr) W us th sam mthod as abov to draw a lin graph btwn RPK and tim, and calculat th rlationship of two variabls as: y2 = a1 + a2 W do th curv fitting in th tool of cftool in Matlab, and gt th rasonabl fitting rsults. Th fitting function is providd blow, with R=.9841: (( x 26) 2.12) (( x 219) 27.22) y2 = W import data into xcl tabl to draw two curvs. Th lin curv rprsnts th actual statistics of th indicator data, and th smooth curv rprsnts data prdictd by fitting function undr no influnc of Expo. 38

3 旅客周转量统计值 无世博因素影响的旅客 Fitting curv 周转量发展趋势 RPK (Millon popl km) 旅客周转量 ( 亿人 公里 ) Fig. 2 As can b sn from th chart, th passngr turnovr improvd significantly aftr 24, which also shows that th traffic in Shanghai has bn grat progrss in dlivry systms. As prdictd curvs and th fittd valu of th actual statistics producd a hug gap aftr 25, thrfor, RPK bcoms a larg aspct impactd by Expo in transportation systm of Shanghai. Aftr statistics calculating, th valu of th Expo impact on RPK is I = Cargo Volum Drawing a lin graph btwn Cargo volum and tim, calculat that th rlationship of two variabls as: ( b x) y3 = a W do th curv fitting in th tool of cftool in Matlab, and gt th rasonabl fitting rsults. Th fitting function is providd blow, with R=.9762: (.5492 x) y3 = W import data into xcl tabl to draw two curvs. Th lin curv rprsnts th actual statistics of th indicator data, and smooth curv rprsnts data prdictd by fitting function undr no influnc of Expo 货物运输量统计值 无世博因素影响的货物 Fitting curv 运输量 Cargo volum 货物运输量 (Millon( 万吨 tons) ) Fig. 3 Th goods traffic was stady incras in 97-8 yars of growth, spcially aftr th succss of th Shanghai Expo application.but th data of 29 dcrasd compard with that of 28, which may b affctd by conomic crisis. Aftr statistics calculating, th valu of th Expo impact on cargo volum is I = Cargo Turnovr Drawing a lin graph btwn Cargo turnovr and tim, calculat th rlationship of two variabls as: y4 = a1 + a2 W do th curv fitting in th tool of cftool in Matlab, and gt th rasonabl fitting rsults. Th fitting function is providd blow, with R=.9766: (( x 26) 5.698) (( x 28) 76.42) y4 = W import data into xcl tabl to draw two curvs. Th lin curv rprsnts th actual statistics of th indicator data, and smooth curv rprsnts data prdictd by fitting th function undr no influnc of Expo. 39

4 货物周转量统计值 无世博因素影的货物周 Fitting curv 转量发展趋势 Cargo turnovr 货物周转量 (Millon tons km) ( 亿吨 公里 ) Fig. 4 Th sam as cargo volum, th data of 29 dcrasd compard with that of 28, which may b affctd by conomic crisis. Aftr statistics calculating, th valu of th Expo impact on cargo turnovr is I = Port Cargo Throughput Drawing a lin graph btwn port cargo throughput and tim, calculat th rlationship of two variabls as: y5 = a1 + a2 W do th curv fitting in th tool of cftool in Matlab, and gt th rasonabl fitting rsults. Th fitting function is providd blow, with R=.9958: (( x 29) 5.466) (( x 295) 16.6) y5 = W import data into xcl tabl to draw two curvs. Th lin curv rprsnts th actual statistics of th indicator data, and smooth curv rprsnts data prdictd by fitting function undr no influnc of Expo 港口货物吞吐量统计值 无世博影响的港口货物 Fitting curv 吞吐量发展趋势 " Port cargo throughput 港口货物吞吐量 ( 万吨 ) (Millon tons) Fig. 5 Aftr statistics calculating, th valu of th Expo impact on port cargo throughput is I = Importanc Wight for th Comprhnsiv Impact of Expo 3.1 A modl of importanc wight Thr ar m indxs:a 1, A 2,, A m. according to th spcific maning of diffrnt indicators and Saaty comparison laws, w got th comparison matrix btwn diffrnt importanc wights: a11 a12 a1 m a21 a22 a 2m 1 A = with aii = 1, aij = a ji am1 am2 amm In th m m matrix, a ij mans that th division btwn th importanc of th i indicator and th importanc of j indicator. Saaty comparison scals 4

5 Scals Tabl 1 Maning 1 Th importanc of A i is qual to th on of A j 3 Th importanc of A i is littl strongr than th on of A j 5 Th importanc of A i is strongr than th on of A j 7 Th importanc of A i is much strongr than th on of A j 9 Th importanc of A i is absolut strongr than th on of A j 2,4,6,8 Th importanc lvl of A i and A j is btwn th lvls abov W calculat th largst ignvalu of comparison matrix λ, and do th consistncy tst. Consistncy indx of A is λ m CI = m 1 Consistncy ratio of A is: CI CR = RI Th valu of RI (Random Indx) is providd in this following chart: m RI If CR<.1,A is rasonabl, and th Eignvctor to Eignvalu λ is α ( α α α ) valu of th importanc wight vctor is: α 1 2 m ( w1, w2,, wm ) = (,, ) m m m α α α α α i i i i= 1 i= 1 i= 1 = 1, 2,, m. And th 3.2 Th importanc wights of transport impact W stablish and calculat th comparison matrix for importanc wights of fiv indicators in transportation: A = 1 1/ /2 1/3 1/ /3 1/3 1/2 1/2 1 And th importanc wights of th fiv indicators of traffic volum ar offrd as blow: ( w, w, w, w, w ) = (.255,.36,.231,.119,.89) W hav alrady obtaind impact of Expo on transportation on avrag: (,,,, ) ( 7.14% 62.3% 6.17% 5.4% 7.72% ) P = I I I I I = Basd on th abov rsults, w gt th ovrall impact of Shanghai Expo on transportation industry: I = wi 1 1+ w2i2+ w3i3+ w4i4+ w5i5= Conclusions In this papr, th impact rat that Expo brought to Shanghai transport rachd 3.25%. And w can us this assssmnt modl to valuat mor industris basd on th statistics data. It can b sn that th Shanghai World Expo has alrady had a hug impact on th transportation conomy. In this papr w us data on an annual basis to stablish th modl. Th advantag of th modl is its obvious long-trm trnds, but th 41

6 drawback is that tourism rvnu which is snsitiv to tim priod will mak th modl blurrd and lack of accuracy. According to th mathmatical modl, w prdict that radiation ffcts on th surrounding ara is profound, pulling conomic growth of th surrounding aras and upgrading of th lvl of consumption, improving th dvlopmnt of trtiary industry. Expo mad contribut to Shanghai's industrial rstructuring, whil promoting th Yangtz Rivr Dlta transportation srvics industris. Bcaus of th SARS in 23 and financial crisis in 29, th data ar anomalis in ths yars which affct our analysis. 5. Rfrncs [1] G. Q. Dai, J. G. Bao. Quantitativ Effcts Assssmnts of Expo 99 Kunming:Modl of Background Trnd Lin. Scintia Gographica Sinca. 27, 27(3): [2] G. N. Sun. Fundation and significanc of background trnd lin of tourists from abroad in China. Scintia Gographica Sinca.,18(5): [3] J. Su. Xinjiang Transport industry and th coordination of tourism dvlopmnt. Northrn Economy. 21,6:52-53 [4] X. J. Liu and L.Shn. Indicators and Comprhnsiv Appraisal Systm for Saving Socity. Journal of Natural Rsourcs. 26,21(3): [5] Z. Shng, and S. Q. Xi, and C. Y. Pan. Probability and Mathmatical Statistics. Publication plac: Highr Education Prss, Fourth Edition,