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Water Environment Quality Analysis Based on Information Diffusion Theory and Fuzzy Neural Network

机译:基于信息扩散理论和模糊神经网络的水环境质量分析

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Reservoirs play a key role in many infrastructure functions for people like flood control, irrigation, and water supply. In this work, we focused on the water quality evaluation model for Shimen Reservoir. Based on the monthly changes of factors such as pH, nitrate, ammonia nitrogen (NH3-N) and total nitrogen (TN) in 2013 and 2014, the information diffusion theory and fuzzy neural network technology were utilized to evaluate the water quality comprehensively. The probability distribution of these four factors in the reservoir was analysed and the water quality of the reservoir evaluated. The results show its reliability and these two methods can provide a basis for water quality control of Shimen Reservoir. Furthermore, the methods can be universally applied to the analysis and research of water quality in other regions.
机译:水库在许多基础设施功能中发挥着关键作用,适用于防洪,灌溉和供水等人。 在这项工作中,我们专注于石门水库水质评价模型。 基于2013年和2014年的pH,硝酸盐,氨氮(NH3-N)和总氮(TN)的每月变化,利用信息扩散理论和模糊神经网络技术全面评估水质。 分析了储层中这四种因素的概率分布,评价了储层的水质。 结果表明其可靠性和这两种方法可以为石油水库提供水质控制的基础。 此外,该方法可以普遍应用于其他地区水质的分析和研究。

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