Safety Evaluation of Highway in Mountainous Area Based on Fuzzy Neural Network

Safety evaluation of highways in mountainous areas has multi-attributed, decision-making problems, which the preference information of the decision maker is not known a priority. In this paper, based on the principle of rank consistency, the ordering chain comparison method will be used for determining weight vector and memberships. This makes the weight more consistent with the actual situation. Using the learning algorithm in BP neural network and comprehensive decision-making model, it gives the fuzzy comprehensive decision method a base on the neural network model of weight adjustment. The use of this method makes the weight more objective and exact, and gives the weight to the self-learning function. In this paper, the use of this method in comprehensive evaluation of highways in mountainous areas has led to satisfactory results. This method can effectively solve the traffic safety evaluation.