A pretreatment method of industrial saline wastewater based on Artificial Intelligence based fuzzy neural network analysis was proposed to improve the pretreatment accuracy of industrial saline wastewater. This method uses a four-layer AI fuzzy neural network model and proposes a graded fuzzy neural network model for pretreatment method of industrial saline wastewater, it includes input layer, fuzzification layer, fuzzy logical layer and output layer, and designs the framework and calculation mode of the fuzzy function block and the neural network module. Finally, the dynamic simulation experiments of dissolved oxygen control in the fifth zone and nitrate nitrogen control in the second zone are carried out based on the simulation benchmark model (BSM1) platform. The experimental results show that this approach can effectively raise the adaptive control accuracy of the system compared with PID, feed forward neural network and conventional recurrent neural network.

中文翻译：

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基于人工智能和模糊神经网络系统的废水预处理方法

为了提高工业盐废水的预处理精度，提出了一种基于人工智能的模糊神经网络分析的工业盐废水预处理方法。该方法采用四层AI模糊神经网络模型，为工业盐废水的预处理方法提出了分级模糊神经网络模型，包括输入层，模糊化层，模糊逻辑层和输出层，并设计了框架和计算模式模糊功能块和神经网络模块的功能。最后，基于模拟基准模型（BSM1）平台进行了第五区溶解氧控制和第二区硝酸盐氮控制的动态模拟实验。