Building Logistics Cost Forecast Based on Improved Simulated Annealing Neural Network

The building logistics cost forecasting is a complicated nonlinear problem, due to the factors that influence building logistics cost are anfractuous, and it was difficult to describe it by traditional methods. So a modeling and forecasting method of building logistics cost based on improved simulated annealing neural network (ISANN) is presented in this paper. First the simulated annealing algorithm with the best reserve mechanism is introduced and it is organic combined with Powell algorithm to form improved simulated annealing mixed optimize algorithm, instead of gradient falling algorithm of BP network to train network weight. It can get higher accuracy and faster convergence speed. We construct the network structure, and give the algorithm flow, and discussed and analyzed the effect factor of building logistics cost. With the ability of strong self-learning and faster convergence of ISANN, 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.