A Combined Model for Regional Eco-environmental Quality Evaluation Based on Particle Swarm Optimization-Radial Basis Function Network

摘要

The eco-environmental quality assessment is a complexity of fuzzy system with multiple indicators and classes,and there are still some limits of radial basis function network evaluation method,so radial basis function network and particle swarm optimization algorithm are combined to establish an improved radial basis function network comprehensive evaluation method for eco-environmental quality assessment. Main limits of radial basis function network are how to choose parameter in the model,so in this method,through optimizing the parameters of the radial basis function by particle swarm optimization algorithm,a neural network model of regional ecological environment is generated to enhance the performance. Additionally,a visualization system of the ecological quality assessment is developed using ArcGIS software,which can be used to display and evaluate the ecological quality of eco-environmental quality. The eco-environmental quality assessment in Sichuan Province of China is taken as an example,and the results show that radial basis function network optimized by PSO is superior to the traditional model,GIS can inquire and display the message and evaluation results,and the hybrid method provides a new approach for the protection and scientific management of ecological quality and worth to be recommended.