Building Logistics Cost Forecast Based on High Speed and Precise Genetic Algorithm Neural Network

The building logistics cost forecasting was a complicated nonlinear problem, due to the factors that influence building logistics cost are anfratuous, and it was difficult to describe it by traditional methods. So a modeling and forecasting method of building logistics cost based on high speed and precise genetic algorithm neural network is presented in this paper. The high speed and precise genetic algorithm neural network is combined the adaptive and floating-point code genetic algorithm with BP network which has higher accuracy and faster convergence speed. We constructed the network structure, and discussed and analyzed the effect factor of building logistics cost. With the ability of strong self-learning and faster convergence of high speed and precise genetic algorithm neural network, the modeling and forecasting method can truly forecast the building logistics cost by learning the index information. The actual forecasting results show that this method is feasible and effective.