模糊神经网络模型在拟建项目环境质量评价中的应用

由于评价因子与环境质量标准之间的模糊关系,导致传统的评价模型结果的不确定性。本文将模糊理论和神经网络模型相结合,利用模糊理论的隶属度反映各因子的质量相对状态,从而更精确地识别模糊性。通过模糊神经网络模型对环境质量标准样本的学习和测试,得出评价等级,并与模糊综合评价方法进行对比,实验结果表明,模糊神经网络模型用于环境质量评价是可行的,且比模糊综合评价方法更为客观、合理。

Application of Fuzzy Neural Network Model in Environment Quality Evaluation of Proposed Projects

The ambiguity existing between evaluation factors and environment quality standards lead to the uncertainty of the results of traditional evaluation model. This paper combined neural network model and fuzzy theory, used menbership degree of fuzzy theory to reflect the quality relative state of each factor. Thus, fuzziness could be recognized more precisely. Through the test of fuzzy neural network model on environmental quality standard samples, get evaluation grade, and compared with integrated fuzzy evaluation method. The result showed that the fuzzy neural network model was feasible in environment quality evaluation and the evaluation result was more objective and reasonable than integrated fuzzy evaluation method.