BP人工神经网络模型在西鞍山铁矿地下水水质评价中的应用  

Application of BP Artificial Neural Network Model in Groundwater Quality Evaluation of West Anshan Iron Mine

作　　者：岳丹丹[1] 梁海涛[1] 王天慧[1] 徐韬[1] 

机构地区：[1]沈阳建筑大学市政与环境工程学院,辽宁沈阳110168

出　　处：《环境监测管理与技术》2016年第4期23-26,共4页The Administration and Technique of Environmental Monitoring

基　　金：国家自然科学基金资助项目(41072190);环保公益性行业科研重大专项基金资助项目(201009009)

摘　　要：以西鞍山铁矿为例,采用BP人工神经网络模型对区内12个监测点的水质进行评价。以枯水期水质监测的主成分总硬度、溶解性总固体、硫酸盐、氯化物、铁和锰、硝酸盐、氟化物指标作为评价因子,建立地下水评价指标体系,并将评价结果与模糊综合评价法及综合质量评价法的评价结果比较。结果表明,8、9、10、11号监测点属于Ⅰ类水,1、2、3、4、6、7、12号监测点属于Ⅱ类水,5号监测点属于Ⅲ类水,西鞍山铁矿的开采未对地下水造成影响;该方法与模糊综合评价法及综合质量评价法的评价结果基本一致,可以客观、合理性地评价水质。Taking West Anshan Iron Mine for exam ple, the BP artificial neural network model was used toevaluate the water quality of 12 monitoring points in the area. The established model took principal componentssuch as total hardness, dissolved total solids, sulfate, chloride, iron and manganese,nitrate, and fluoride asevaluation factors. Comparing with the evaluation results by fuzzy comprehensive evaluation method andcomprehensive quality evaluation m ethod, results showed that the water quality in site No. 8,9, 10 and 11 wereup to standard of class I , in site No. 1 , 2 , 3 , 4 , 6 , 7 and 12, up to class I I , and site No. 5 , class HI,indicating the West Anshan Iron Mine had no impacts on the groundwater quality. The results evaluated by theestablished method were in accordance with the results by the two methods mentioned above. Therefore,objective and reasonable evaluation results can be made by the established method.

关 键 词：人工神经网络 地下水 水质评价 西鞍山铁矿 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程] X824[自动化与计算机技术—控制科学与工程]