投影寻踪和BP网络在农村饮用水水质评价中的应用

日渐严重的农村饮用水水源污染问题已经影响到人们的日常生活,对水质变化情况的及时了解并针对其综合状况进行合理评价十分必要。根据农村饮用水水源地特点,选取了粪大肠杆菌、氨氮、总磷、高锰酸盐指数、溶解氧5个主要污染物作为评价指标,建立投影寻踪等级评价模型,计算水质标准等级与水质样本投影值,通过比较投影值得出样本等级。然后用BP神经网络对样本及投影值进行学习并预测,验证计算结果的合理性。以安徽省定远县的11个地表水水源地丰水期和枯水期水质进行实际评价。计算结果表明:与常用评价方法相比,模型准确有效,可为水质综合评价提供新方法。

Application of projection pursuit and BP neural network in assessment of drinking water quality in rural areas

The increasingly drinking water pollution in rural areas have affected people''s life. To capture the variation timely and to evaluate the water quality conditions based on monitoring data are of great importance. Based on the rural drinking water source characteristics, 5 major pollutants were selected as the evaluation indexes which included fecal coliform, ammonia nitrogen, total phosphorus, permanganate index and dissolved oxygen, respectively. Projection pursuit evaluation model was established to evaluate water quality standard level and pursuit values of water samples. Then the two projection values would be matched to evaluate the levels of samples. BP neural network was used to study and predict the calculation results and test the rationality 11 surface water quality samples of Dingyuan County in Anhui Province during the wet and the dry seasons were collected for assessement. The results showed that, compared with common assessment methods, this model was of great accuracy and validity, which provided a new way for the comprehensive evaluation of water quality.