Evaluation of the Application of BIM Technology Based on PCA - Q Clustering Algorithm and Choquet Integral

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Risk Evaluation Of Expressway PFI Construction Project Based On the Analytic Hierarchy

Process and Grey Clustering

HONG Wen-xia ,WEI Xiao-zhao,YANG Fan

(Qingdao University of Technology, Qingdao, Qingdao, Shandong 266520)

Email: [email protected]

Keywords: analytic hierarchy process; grey clustering algorithm; PFI financing model; highway

project

Abstract. This paper analyzes the advantages of PFI project and the feasibility of highway

construction project, analyzes the risk factors and the project stakeholders, and establishes the risk

factors involved in the construction project, and establishes a risk assessment system, and uses the

analytic hierarchy process to calculate the weight of the evaluation index, and then improve the

objectivity of the evaluation system. The main body of the financing is involved in the cluster analysis,

quantitative analysis, and through the gray clustering algorithm to evaluate the risk index value, and

finally quantitative analysis of PFI financing mode in the highway construction projects in the use of

integrated risk.

0 Introduction

The highway construction project is one of the main contents of the city public construction project,

the external security characteristics and earnings stability. With the development of urbanization, the

demand of highway projects is also increasing, the government can not be a shortage of funds,

long-term and effective financial management of highway project, commissioned by the local

government in general, but the high cost of construction the heavy burden of government. The PFI

(Private Finance Initiative, PFI) provides higher efficiency because it can lower costs, public service

products, which has aroused wide attention, in the era of economic globalization, governments around

the world in all kinds of public infrastructure projects to actively seek private capital, improve the use

of the efficiency of social liquidity, but also broaden the financing channels for the government (in

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IETI Transactions on Computers, 2016, Volume 2, Issue 3, 137-144.

http://www.ieti.net/tc

An International Open Access Journal

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Figure 1 Example 1

1 highway construction project under PFI mode

PFI (Private Finance Initiative) refers to the government to take measures to attract private sector

participation in public investment projects, the use of private sector of their own funds, technology,

operation, management of government for products and services, government and private joint

operation, to achieve the efficiency of public goods, resources optimization. To implement concrete

highway construction project the government, after the completion of the highway to return to attract

private capital, the private sector to complete the project management life cycle from development to

completion, after the expiration of the contract, by the government to recover the final products and

services. This mode of financing greatly ease the financial pressure of the government, but also to

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2 construction of risk assessment model

2.1 construction of evaluation index system

Mainly involved in highway construction projects from the role of government, item company (SPV),

contractors, suppliers, design units, supervision units, financial institutions and other major

stakeholders in the project. Whether to participate in the specific project stakeholders of the risk

depends on the highway construction projects. This paper mainly through the project stakeholders

since the project began to get involved in all the corresponding return time periods considering the

risk, to provide various services of project stakeholders, resources, capital, risk environment may be

involved to calculate the risk type of. PFI project financing process, a reasonable allocation of risk

factors related to the success of the whole project. In this paper, fully consider the risk of project

stakeholders sharing and control perspective, to ensure the reasonable operation of the project.

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2.2.1 analytic hierarchy process to calculate the weight of each risk assessment index

AHP method is subjective and objective combined evaluation and decision method. Its purpose is

the decision problem, decision-making process, decision-making level to carry on the analysis,

decision model is established, through the combination of qualitative evaluation and quantitative

calculation method, the theory of hierarchy has been quantified, and decision-making to solve the

problem of multi scheme.

2.2.2 determine the grey value of whitening weight function

Through calculating the different clustering clustering target different indicators have different

whitening value, then a gray value of statistical analysis. The comprehensive results clustering target

and the final results are inextricably linked. Because the research object is the evaluation of risk

factors of PFI under the mode of the highway construction project, the goal will be for clustering the

risks involved in the object is different, the risk assessment index system of the corresponding

clustering index is the risk of object. In this paper, the index of risk factors (i.e. clustering index)

represented by Uij, among them (i=1,2,3,4..m, j=... 1,2,3,4...N), L grey said it would risk factors is

divided into L grade level. Gray value represents a an interval number in the theory of gray clustering,

dynamic clustering evaluation is a partition. Albino interval values are determined by expert scoring

method, due to the association between the corresponding gray value is not the same, so whitening

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2.2.3 cluster analysis and evaluation

takeijRepresents a clustering evaluation of the I expert on the first j grey class, available：







 _k

k j k j

i f (xij)w

5

1

 1

2.2.4 establishes the cluster model and carries on the grey clustering analysis

set upiA clustering model is set up to represent the I expert.：i(_i₁,_i₂,..._i₅)

The grey value of clustering index is determined according to the maximum degree of membership.：



k



i K k

i MAX 



5 1 *

 

 2

I It belongs to the category of grey indexK*。

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142 3.1 examples illustrate

According to the design of the PFI financing pattern of a certain expressway project in Baoji,

Shaanxi Province, the grey value judgment matrix is determined by the expert scoring method.

Therefore, it can be calculated that the relative weights of various indicators are as follows:

WU1=(0.6283,0.1492,0.2370)T

WU2=(0.4032,0.5171,0.2134)T

WU3=(0.5476,0.4175,0.1267)T

WU4=(0.5212,0,1234,0.2879)T

WU5=(0.2133,0.4132,0.0000)T

WU6=(0.5000,0.5000,0.0000)T

WU7=(0.6522,0.2100,0.2100)T

3.2 grey cluster index

4 experts were asked to rate the grey clustering index, and the results were analyzed by cluster

analysis, the results showed as follows.

Table 1 risk factors of grey index

Clustering index Expert

Expert1 Expert2 Expert3 Expert4

U11 2 1 1 2

U12 1 2 1 1

U13 3 4 4 3

U21 3 3 4 2

U22 2 3 3 2

U31 3 2 2 3

U32 4 3 2 3

U33 2 1 2 2

U41 1 2 1 2

U42 2 1 2 3

U51 3 1 3 1

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U53 1 1 2 1

U61 2 2 1 3

U62 3 4 3 4

U71 2 2 3 2

U72 3 1 2 1

U73 2 3 3 2

4 conclusions

Through the example analysis can know, analytic hierarchy process and grey whitening weight

function can fully assess the PFI project, project managers take full account of PFI risk factors provide

the necessary theoretical basis, also accumulated sufficient experience for the future of the PFI project

risk management.

References

[1] Liu Hong. The application of PFI in the financing of infrastructure construction in small cities and

towns [D]. Xihua University, 2011

[2] Jin Yucheng, Li Ming. Application of PFI financing model in small town water industry project

[J]. southwest water supply and drainage, 2009,02:44-48.

[3] Ma Lin. PFI model risk management research [D]. Southeast University, 2006

[4] Du Wenyuan. PFI project decision making and bidding evaluation method research [D]. Tianjin

University of Technology, 2006

[5] Li Zhengwei. Study on PFI model of pension real estate [D]. Chongqing University, 2013.

[6] fee. Enterprise infrastructure financing of Chinese small towns of [D]., Northwest Agriculture and

Forestry University, 2004

[7] Chen Long, Liu Zheng. Application of PFI model in the development of small cities and towns [J].

Heilongjiang Social Sciences, 2013,05:44-47+2.

Author introduction:

Wei Xiaozhao (1991-), male, graduate student. Research direction: Civil Engineering and

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Hong Wenxia (1964-), female, master's degree. Title: Qingdao Technological University, Professor,

master's tutor. Research direction: Civil Engineering and engineering cost management. Work unit:

Qingdao Technological University.

Contributor contact: Wei Xiaozhao Tel: 18766215697

Contributor mailbox: [email protected]

Mailing address: Qingdao Economic Development Zone No. 2 Changjiang River (old campus of