基于BP神经网络方法的矿业城市可持续发展综合评价模型

正确合理的评价矿业城市可持续发展，对决策部门制定可持续发展方案提供依据具有重要的意义。本文采用层次分析法从经济环境、资源、社会发展4个方面，构建了评价矿业城市可持续发展水平的评价指标体系；通过分析比较目前可持续发展程度的各种评价方法，在充分考虑各种评价方法的特点和矿业城市的特点的基础上，提出了基于神经网络的综合评判方法，并据此建立了三层B—P神经网络评价模型。最后，通过实例证明，指标的选取和神经网络评价模型都比较合理。

BP NEURAL NETWORK BASED APPROACH TO SYNTHETICAL EVALUATION MODEL OF SUSTAINABLE DEVELOPMENT IN MINE CITIES

Reasonable evaluation for sustainable development in mine cities is important to management department making policy.The paper constructed the indexes system of the assessment of mining cities sustaining development level from the aspects of economy,environment,resource,society and population through using hierarchy analysis.Through comparison various methods for the sustainable development are analyzed.On the basis of considering advantages of the methods and characteristics of the mining cities,the state trend evaluating method of Neural Networks Synthetical is put forward,and established three layer's B-P Neural Network evaluation model.It is showed by examples that the choosing of indexes and methods are reasonable.