A Study On Fuzzy Neural Networks In Rural Road Cost Estimation Model

Rural road is an important part of the development of national transportation network and is important to the development of rural economic infrastructure. Since the "the tenth five-year program", our country has largely increased the amount of money spent on the development of rural road. With the continuous increase investment and construction projects, the rural road construction cost often appears lost of control. The major reason for this is the insufficient accuracy of investment forecast. Therefore, it is extremely essential of establishing a fast, accurate estimating method.As the gradual establishment of the management information system of the national Rural road construction project cost, it provides data support to rapid cost estimation model. Approaching through a systematic method of neural network and emphasising on the characteristics of road construction cost, this paper explores the model of a rapid establishment of rural road cost. The main research work and innovation are:it is the first the rapid cost estimation model that is based on the neural network and fuzzy mathematics used in the cost estimation of rural road construction. In order to predict the cost, the engineering characteristics of the rural highways were linked to the project cost through the model. During the selection of engineering properties that affect the model, I tried to fit the actual situation of rural roads in order to achieve optimal results.