CAJ | 학술논문

为了保证城镇居民饮水安全，针对水质分级标准存在的模糊性，引入模糊神经网络理论，建立水环境质量评价模型。选取吉林省白山市白云峰水库为研究区，通过调查采样选定6处监测点，将其模型评价结果与尼梅罗综合指数法的评价结果进行对比分析。结果显示，模糊神经网络评价水环境质量是可行的，水质评价结果精度更准确，打破了传统方法的局限性。模糊神经网络模型具有较强的学习能力，能够提高地下水水质评价的准确性，为日后保护和管理水环境提供了科学依据。
위료보증성진거민음수안전，침대수질분급표준존재적모호성，인입모호신경망락이론，건립수배경질량평개모형。선취길림성백산시백운봉수고위연구구，통과조사채양선정6처감측점，장기모형평개결과여니매라종합지수법적평개결과진행대비분석。결과현시，모호신경망락평개수배경질량시가행적，수질평개결과정도경준학，타파료전통방법적국한성。모호신경망락모형구유교강적학습능력，능구제고지하수수질평개적준학성，위일후보호화관리수배경제공료과학의거。
In order to ensure the safety of drinking water for urban residents, the fuzziness of classification of water quality stan-dard, introduce the fuzzy neural network theory, establish the model of water environment quality evaluation. Selects the Jilin province Baishan City baiyunfeng reservoir as a study area, by sampling selected 6 monitoring points, the evaluation of the model evaluation results and the Nemero index analysis and comparison of results. The results showed that, fuzzy neural network evalua-tion of water environment quality is feasible, water quality evaluation result more accurate, to break the limitations of traditional methods. The model of fuzzy neural network has strong learning ability, can improve the accuracy of groundwater quality evalua-tion, provided the scientific basis for the protection and management of water environment.