An Early Risk Warning Study Of Highway Construction Based On Artificial Neural Network

In recent years, with the unceasing development of Chinese highway’s construction, varieties of questions are constantly coming out and they are very likely related to the success or failure of the whole project. Therefore, in order to identify the the main risks and take measures to lower the influence of the project construction effectively, it is urgent to do warnings to the whole project. In order to lower the construction unit damage effectively, the article established the highway construction project risk early warning system which based on artificial neural network.According to the engineering project of the principle and implementation procedures early warning, and combine the characteristics of the highway engineering construction of highway engineering construction risk early warning was studied, and the main results of the research are as follows:Firstly, the paper builds up the suitable highway project construction warning system structure, and establishs the the four main steps of the program warning system.They were warning influence factor analysis, risk early warning index determination, the determination of the risk level and the determination of coping mechanisms.Secondly, according to the highway engineering construction’s large scale, more procedures, organization and coordination work complex, huge investment and influenced by the huge complex external conditions and various problems of highway construction’s management process, the paper analyses the six factors:time delay, engineering quality defects, high cost, profit decline, environmental protection and sustainable development.Thirdly, establish the risk early-warning index evaluation system. Take the six main influence factors as the input of the early warning system, and according to the former construction experience using the experience of the six modes will do a quantitative index and get the treatment of their value. And according to the former construction experience of serious degree according to risk a hierarchy, from serious to not serious degree of the corresponding p level respectively for red, orange, yellow, green and blue.Fourthly, in the determination of the risk level stage, the paper takes six index through the quantization process as artificial neural network’s input layer based on artificial neural network the basic structure, after calculate the output layer are the calculation results which are the finally result of the the determination of the risk level. And then take remedical measures based on the risk response mechanism coping mechanisms in order to avoid the risks of the project for the loss caused by the further enlargement. Fifthly, the paper takes the highway construction of Yantai port for empirical research object, verified the research result of the thesis has practical value. According to the construction of the main risk factors and the paper established risk early warning index system, and yantai port on the highway construction risk level p forecast, determine its p level green, namely lower risk level, and formulated a certain risk response measures.