应用B—P神经网络的城市空气污染预测研究  

Research on A Kind of Urban Air Quality Forecast Model Based on BP Neural Network

作　　者：韩道汶[1] 吴笛[1] 李丽 

机构地区：[1]济南市环境保护科学研究所 [2]山东省劳动职业技术学院,山东济南250014

出　　处：《中国环境管理干部学院学报》2007年第4期70-73,共4页Journal of Environmental Management College of China

摘　　要：在具有城市重点污染源的排放数据的条件下,利用人工神经网络的自学习、自组织、自适应和较强容错性等特点,探讨B-P神经网络应用于城市空气质量预测的适用性。试验结果表明:此种方法基本适用,且在污染源监测数据充足的基础上,预测结果会更加准确。Under the terms of having continuous monitoring data of urban key pollution sources, this article discusses the feasibility of B-P nerve network technology for urban air quality forecast by B-P nerve network technology＇s advantages of self-study, self-organization, self-adoption and unusual fault tolerance. Results shows： This method is generally applicable, and the prediction results will be more accurate if monitoring data is enough.

关 键 词：B—P神经网络 空气质量 预测 

分 类 号：X831[环境科学与工程—环境工程]