Evaluation of the Effectiveness of Collusion Control Policy Implementation by BP Neural Network Based on Annealing Algorithm Optimization

Author:

Ma Chongsen1ORCID,Chen Yun1ORCID,Lei Zeyang1ORCID

Affiliation:

1. School of Traffic & Transportation Engineering, Changsha University of Science and Technology, 410000 Hunan, China

Abstract

Due to the national economic development form and social development demand, in recent years, the government has been vigorously promoting the control of government-enterprise collusion in the bidding process of government projects in order to promote the standardization of the market. How to predict the vertical collusion behavior under different internal and external environments has become an important research content. Although the prediction of individual behavior is difficult to achieve, the prediction of group behavior has certain possibilities. In this paper, we propose a method for predicting and evaluating the vertical collusion behavior of government investment project bidding based on BP neural network analysis optimized by an annealing algorithm. First, drawing on the traditional evaluation model, the evaluation index system of government-enterprise collusion behavior is constructed from five dimensions: internal environment, external environment, policy development, enforcement effort, and feedback channel. Secondly, a machine learning method based on BP neural network optimized by an annealing algorithm is introduced to evaluate the influence of the change of initial conditions on the bidding collusion behavior. This study has certain significance for government managers to discover the problems and causes in policy formulation, which in turn can support the government in further improving the policy utility.

Funder

National Natural Science Foundation of China

Publisher

Hindawi Limited

Subject

General Engineering,General Mathematics

Reference27 articles.

1. Insider information trading corruption: a new corruption trend;C. Yao;Journal of Shanghai University (Social Sciences Edition),2016

2. Research on the identification of collusion behavior of multi-interest subjects in engineering project bidding;J. Chen;Journal of Railway Science and Engineering,2020

3. A study of collusion in government investment projects based on SNA perspective;Le Yun;Journal of Public Management,2013

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