摘要
针对神经网络综合评价模型的解释缺失和信息损失问题,提出了一种引入专家系统和模糊系统的改进模型,模型利用专家系统提供评价结果的合理解释,利用模糊系统减少评价结果的信息损失,旨在提高评价结果的准确性和可信度.讨论了模型的定义和原理,通过模拟验证后,将改进的神经网络综合评价模型应用于大气环境承载力评价,以期为衡量社会经济发展和大气环境的协调程度提供一定参考.
In this paper, we propose a comprehensive novel neural network model incorporating expert system and fuzzy system to deal with the problem of interpretation and information loss in the evaluation study. The proposed model involves the expert system to provide reasonable interpretations for the evaluation result and fuzzy system to reduce the loss of information in the evaluation result. This paper discusses the definition and principle of the proposed model and validates its improvement by numerical simulation. An applied study of the atmospheric environmental capacity is analyzed as an illustration to measure the interaction between socioeconomic development and atmospheric environment.
出处
《数学的实践与认识》
北大核心
2015年第10期59-68,共10页
Mathematics in Practice and Theory
基金
国家自然科学基金青年项目"预测模型的结构化变量选择方法研究"(71301162)
中医药行业科研专项项目"30种疾病中医临床评价规范与复杂干预共同路径研究"(201207665)
中国人民大学科学研究基金项目‘纵向边际化随机效应模型应用研究"(13XNF058)资助
关键词
综合评价
神经网络
专家系统
模糊系统
comprehensive evaluation
neural network
expert system
fuzzy system