Advanced Materials Research Online: 2013-12-13 ISSN: 1662-8985, Vols. 869-870, pp 172-177 doi:10.4028/www.scientific.net/amr.869-870.172 2014 Trans Tech Publications, Switzerland The evaluation research on the rural infrastructure construction of Shaanxi based on Grey-AHP Yin Shengxing 1,a *, Li Huiming 2,b, Wang Aojun 3,c,Sha Meng 4,d 1,2,3,4 Xi'an University of Architecture and Technology, Xi'an, Shaanxi, China a 441401645@qq.com, b ysx123@126.com, c 779676795@qq.com, d 373839962@qq.com Keywords: Shaanxi Province; Rural ; Infrastructure construction ; Gray-AHP ; Evaluation Abstract. The evaluation of the rural infrastructure construction is the premise and foundation of its decision-making. In order to promote the integration and common prosperity of urban and rural development, gradually narrowing the gap between urban and rural areas, and improve the efficiency of the new socialist rural infrastructure construction, this paper analyzed the characteristics of rural infrastructure construction of Shaanxi province based on a large number of visiting to research and classified the rural infrastructure construction of Shaanxi. In the end of the paper, it proposed the Gray-AHP evaluation methods of rural infrastructure construction, which will play a guiding role for rural infrastructure construction of Shaanxi province in future. Introduction Shaanxi is a major agricultural province in the northwest of our country. It has a big proportion of agricultural population, the backward rural development, weak rural infrastructure construction, few complete and scientific evaluation system,and certain blindness in decision-making process. In view of this situation, paper analyzed the present situation of rural infrastructure in Shaanxi province after abundant investigation to set a simple and feasible evaluation index system, which has a certain reference value for decision-making of rural infrastructure construction in Shaanxi in the future. The evaluation index system of rural infrastructure Rural infrastructure is the sum of all kinds of factors to provide public services for the rural economic,social development and it is the basic condition of rural economic, social and cultural development and the farmers life. After careful screening, the rural infrastructure was divided into seven aspects, namely: traffic engineering, water supply and drainage engineering, life engineering, cultural and educational projects, information and communication engineering, medical engineering and health facilities engineering. According to the characteristics and specific classification of rural infrastructure, evaluation index system was divided into four levels as the following table 1. Table 1 Rural infrastructure evaluation index The minor criterion level C C 1 Road engineering The target level A Index level D Unit Explain B 1 Traffic engineering D 1 The proportion of road hardening villages and towns All rights reserved. No part of contents of this paper may be reproduced or transmitted in any form or by any means without the written permission of Trans Tech Publications, www.ttp.net. (#69782854, Pennsylvania State University, University Park, USA-16/09/16,07:03:20)
Advanced Materials Research Vols. 869-870 173 D 2 The proportion of villages and towns getting to the nearest national highway in one hour C 2 Transport infrastructure D3 The proportion of villages and towns that have road safety facilities D 4 The proportion of villages and towns that have stations B 2 Water supply and drainage engineering C3 Water supply facilities D 5 The proportion of villages and towns that centralized water supply D6 The proportion of villages and towns used by pipeline to supply water C4 Drainage facility D7 The proportion of villages and towns that centralized swage treatment B3The energy can be used in daily life C5 Power supply facilities D8 The proportion of project for upgrading urban and rural power grids D9 The proportion of uninterruptible Power Supply in night. C6 New Energy facilities D10 The proportion of villages and towns that using of new energy B4 Cultural and educational projects C7 Cultural facilities D11 The proportion of villages and towns that set up Reading room D12 The proportion of villages and towns that set up recreation room C8 Educational facilities D13 The proportion of villages and towns that set up Primary school D14 The proportion of villages and towns that set up Middle school B5 Information and Communication Engineering C9 Communications facilities D15 The proportion of villages and towns that set up phone facilities D16 The proportion of villages and towns that set up broadband facilities B6 Medical care and social security engineering C10 Medical Facilities D17 The proportion of villages and towns that set up clinic or health room C11 Social security facilities D18 The proportion of villages and towns that set up old folks' home or orphanage B7 Sanitation project C12 Waste disposal facilities D19 The proportion of villages and towns that set up garbage collection facilities the traffic lights, street lamps, etc the train station, bus station, etc Such as Digesters, Solar facilities, etc Landline or mobile phone can be used with the outside world
174 Sustainable Development of Industry and Economy D20 The proportion of villages and towns that set up Centralized waste treatment center C13 Excreta disposal facilities D21 The proportion of villages and towns that set up public toilets D22 The proportion of villages and towns that accomplished outhouse toilet reform water toilet The evaluation model of rural infrastructure based on the Gray-AHP According to the judgement matrix of evaluation index system built by AHP, Grey-AHP calculates the weight of each index and analysizes the situation quantitatively and comparatively. Then it compares the data formed by evaluation objects and the ideal data to get the optimal and worse order of each evaluation object. Thereby, it gets the evaluation results. Grey-AHP is a comprehensive method which conbines the advantages of grey correlation method and analytic hierarchy process to get the optimal and worse order of each evaluation object objectively. The specific steps are as follows: 3.1 To construct the initial judgement matrix Comparison of two indexes on the same level, determine its governed degree under the last index, quantify its important degree according to introduced scale as the following table 2. Table 2 The meaning of the scale Importance Weights Explain ei is extremely important than ej 9 Two indicators reached the maximum extent of difference within the scope of possible range ei is strongly important than ej 7 Two indicators reached strong difference ei is obviously important than ej 5 Two indicators reached obvious difference ei is slightly important than ej 3 Two indicators reached slight difference ei is the same important than ej 1 Two indicators reached no difference ei is slightly unimportant than ej 1/3 Two indicators reached slight difference ei is obviously unimportant than ej 1/5 Two indicators reached slight difference ei is strongly unimportant than ej 1/7 Two indicators reached strong difference ei is strongly unimportant than ej 1/9 Two indicators reached the maximum extent of difference within the scope of possible range aij take the value corresponding to 2,4,6,8,1/2,1/4,1/6,1/8,If the difference degree of ei and ej is between two adjacent level 3.2 Calculating the weight of e n According to the obtained matrix A, supposed A has the consistency. Calculating its maximum eigenvalues and the eigenvector ω(ω 1,ω 2,,ω n ) corresponding to the eigenvalue. ω i = ω i (i=1,2,,n),thus ω n (ω 1,ω 2,,ω n )is e n ( e 1,e 2,,e n ) s target weight. n i=1 ω i 3.3 To check the consistency of judgement matrix For judging matrix A degree of consistency, we introduced index CI: CI= λ max n n 1 λ max the maximum eigenvalue of the matrix A n the dimensions of the matrix A (1)
Advanced Materials Research Vols. 869-870 175 The value of index CI is positive correlation with the degree of deviation of matrix. The accuracy of consistency is reduced When the value of n is large, Therefore need to introduce a new indicator CR, CR = CI, RI can be obtained from table 3 RI Table 3 Average random consistency index 1 2 3 4 5 6 7 8 9 0 0 0.58 0.9 1.12 1.24 1.32 1.41 1.45 Notice:When calculates CR<0.10,it generally considered that judgement matrix has consistency degree of deviation can meet the requirements, otherwise you need to adjust the judgement matrix. 3.4 To determine the weight of evaluation index According to the method of the weight of the index relative to the upper index, we can get all the weight of the index relative to its upper index. Finally, we can determine the weight of the last index relative to the initial index ωi. Established the single-index system based on AHP, which within n indicators and m evaluation objects,so the original index data matrix of m evaluation objects is denoted as R. r 11 r 12 r 1n r 21 r 22 r 2n R= [ ] (2) r m1 r m2 r mn 3.5 Select the desired object Get R, we can determine the ideal object R 0, R 0 =(r 0 1,r 0 2,,r 0 n ), (j=0,1,2,,n)is the optimal value of indicator j in all indicators to be evaluated, max, j is the indicator of profit ={ min, j is the indicator of cost (i=0,1,2,,m;j=0,1,2,,n) (3) 3.6 Handle the original data with dimensionless method Because each index represents different meaning, so using the extreme value method to handle the original data with dimensionless method. Processing method is as follows: (4) s ij = {,, is the indicator of profit is the indicator of cost (i=0,1,2, Combining the processing data and the ideal object data to get a new matrix: S= [ n n n,m;j=0,1,2,,n) ] (5) i=( i1, i2,, in ),i=0,1,2,,m, calculating of the correlation coefficient i(j) of the jth idex about i and with treating as the reference sequence. 3.7 Calculating the correlation coefficient matrix Calculating the correlation coefficient βi(j) of the jth index about Si and S0,i=1,2,,m;i=1,2,,n. i(j)= in in s 0j s ij + ρ ax ax s 0j s ij s oj s ij + ρ ax ax s 0j s ij (6) The ρ is the correlation coefficient in the formula above, determining the ρ=0.5,after calculation,we can get the correlation coefficient matrix :
176 Sustainable Development of Industry and Economy (7) 3.8 Calculating the comprehensive evaluation result X X= (8) Among them, ω=(ωi)n 1 is the weight of index level relative to the target level mentioned from above, satisfying inωi=1. X=[xi]m 1 is the comprehensive evaluation result matrix for the number of m evaluation objects. Thus the evaluation result of the jth evaluation object is: X i =[ (1), (2)],, (n)) (9) When xi becomes larger,the ith evaluation object and ideal object becomes closer. It shows that the ith evaluation object is better, so the order of quality of each evaluation object can be obtained. In the end, we can get the evaluation results. The example analysis This paper evaluated the rural infrastructrue construction in Shaanxi province using the above models. The evaluation objects included the northern, the central and the southern region of Shaanxi province. The datas came from China Statistical Yearbook 2012, Shaanxi Statistical Yearbook 2012 and the research. 4.1 Take the data into the evaluation model and select the maximum index of each as the ideal object. That is: R 0 =(r 0 1,r 0 2,,r 0 21 )=(D 1 *,D 2 *,,D 22 *) (10) 4.2 The weight of ω i determined from AHP, ω i = [0.054116, 0.007735, 0.003438, 0.006886, 0.031737, 0.054251, 0.067814, 0.031731, 0.025574, 0.005900, 0.007956, 0.020895, 0.138906, 0.027847, 0.100760, 0.070902, 0.091210, 0.073144, 0.056121, 0.023610, 0.009264, 0.090203] 4.3 Using formula (7) to calculate the correlation degree i, 1=[0.656518, 0.358025, 0.619158, 0.599669, 0.812700, 0.810753, 0.494938, 1.000000, 0.798165, 1.000000, 0.667192, 0.581837, 0.834794, 0.707317, 0.954733, 0.577525, 1.000000, 0.720738, 0.629308] 2=[1.000000, 1.000000, 1.000000, 1.000000, 0.896673, 0.851016,, 1.000000, 0.945522, 1.000000, 0.516230, 1.000000, 0.806735, 1.000000, 0.783784, 1.000000, 1.000000, 0.890456, 1.000000, 1.000000] 3=[0.634717, 0.333333, 0.730429, 0.558982, 1.000000, 1.000000, 0.637363, 0.852624, 0.868263, 0.599028, 0.727742, 1.000000, 0.771098, 1.000000, 0.750809, 0.637363, 0.844217, 0.673752, 0.700085] 4.4 Using formula (9) to calculate the comprehensive evaluation results X, the northern region gets 0.746602, The central region gets 0.94360, the southern region gets 0.777243.
Advanced Materials Research Vols. 869-870 177 Results analysis The above calculation can draw the following conclusion: 5.1 Among the three regions, the northern region gets the lowest score, which suggests that its rural infrastructure construction in Shaanxi is relatively poor. So in the future, great emphasis should be laid on road facilities, water supply, drainage facilities and cultural facilities 5.2 The central region tops among the three regions, the indexes of which get the highest score. It shows that the rural infrastructure in this region works best. Thus the northern region and southern region should learn from the achievements. 5.3 Although the southern region is in the middle level, its development of the rural infrastructure is unbalanced.the road engineering, power supply facilities, education facilities, and garbage disposal facilities are still need to be improved. Conclusion Combine Grey-AHP to the evaluation of rural infrastructure and establish rural infrastructure evaluation model to evaluate the effect of the rural infrastructure construction in Shaanxi province. Suppose that the result of the evaluation model accords with the qualitative analysis result, then it will prove to be scientific. References [1] Fei Zhichong.Entropy - AHP and Grey - Analytic Hierarchy[D]. Tianjin University, 2009 [2] Xiao Tan. Rural Infrastructure Investment Evaluation System Research Of Shaanxi Province [D]. Xi'an University of Architecture and Technology, 2010 [3] Li Fuzhong. The evaluation systems index research on Building a new socialist countryside [J]. Construction Management ModernizationL2006-4 [4] Tan Xiao.The evaluation research on current situation of rural infrastructure[j]. Shaanxi Construction: 2010-5 [5] Wang Shuang. The evaluation systems index research on Building a new socialist countryside of Liao Ning [J]. Statistics and Consulting: 2010-3 [6] Zheng Pingping. The evaluation systems index research and methods on the new socialist countryside [J]. Modern agriculture: 2010-3