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首页> 外文期刊>Journal of Computers >Effluent Quality Prediction of Wastewater Treatment System Based on Small-world ANN
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Effluent Quality Prediction of Wastewater Treatment System Based on Small-world ANN

机译：基于小世界ANN的废水处理系统流出质量预测

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—In order to provide a tool for predicting wastewater treatment performance and form a basis for controlling the operation of the process, a NW multi-layer forward small world artificial neural networks soft sensing model is proposed for the waste water treatment processes. The input and output variables of the network model were determined according to the waste water treatment system. The multi-layer forward small world artificial neural networks model was built, and the hidden layer structure of the network model was studied. The results of model calculation show that the predicted value can better match measured value, playing an effect of simulating and predicting and be able to optimize the operation status. The establishment of the predicting model provides a simple and practical way for the operation and management in wastewater treatment plant, and has good research and engineering practical value.
机译：- 为了提供一种用于预测废水处理性能的工具，并形成控制该过程的操作的基础，提出了一种NW多层前进小世界人工神经网络软感测模型的废水处理过程。根据废水处理系统确定网络模型的输入和输出变量。建立了多层前进小世界人工神经网络模型，研究了网络模型的隐藏层结构。模型计算结果表明，预测值可以更好地匹配测量值，播放模拟和预测的效果，并能够优化操作状态。预测模型的建立为废水处理厂的运营和管理提供了一种简单实用的方式，具有良好的研究和工程实用价值。

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