Bp Neural Network-based Trade Growth And Environmental Damage Prediction

With the economic globalization and trade liberalization to speed up the process, more and more environmental problems caused by the world's attention has become a major human problems. Against the backdrop of economic globalization and the emergence of a series of global environmental problems has become a constraint on economic, social and sustainable development of the barrier. With China's rapid trade growth, increasing environmental damage, the study of environmental damage and trade growth forecast for the issue of trade policy formulation and coordination, environmental policy, industrial policy is of great significance.In this paper, carding a theory of the relationship between trade and environment, introduced the neural network's basic theory, focuses on BP neural network models and structures, BP algorithm and its improvement, construction of the trade growth of the environmental damage caused by BP neural network model, neural network Models were used in forecasting and time series data panel predicted that the use of MATLAB tool for the realization of the simulation model for environmental damage caused by trade issues forecast.Trade growth and environmental damage the relationship between the latitude is more complicated, in today's international economics an important area. The traditional method of forecasting more difficult to solve the increasingly complex and volatile issue economic forecasts, in order to explore the neural network system for trading pollution caused by the possibility of early warning, previous studies in this paper, on the basis of the information on the use of large-scale Parallel processing with learning and memory functions of the neural network model to simulate the trade and environment between the complex relationship between BP neural network to verify the prediction method has been applied to the growth of trade and environmental damage the effectiveness of the prediction. The model used in Chinese trade and environmental pollution forecast results show that the model has the necessary samples less accurate, simple calculation, etc., to study the environmental pollution caused by the trade forecast to provide a new way.