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- W2896629395 abstract "Due to the complex dynamic behavior in wastewater treatment process, online measurement of ammonia nitrogen value is very difficult. In this paper, a case-based reasoning (CBR) prediction model based on a feedforward neural network (FNN) is introduced to predict the effluent ammonia nitrogen value. First, easily measured feature variables which have great effect on effluent ammonia nitrogen value were selected. Next, the prediction model was established, and attribute weights in case retrieval were determined by the connection weights of a trained FNN. Finally, based on the data in a real wastewater treatment process, simulation experiments were carried out. The results show that the prediction model using FNN-based CBR is effective and has better prediction accuracy than some other methods." @default.
- W2896629395 created "2018-10-26" @default.
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- W2896629395 date "2018-07-01" @default.
- W2896629395 modified "2023-09-25" @default.
- W2896629395 title "Prediction of Effluent Ammonia Nitrogen Using FNN-based CBR" @default.
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- W2896629395 doi "https://doi.org/10.23919/chicc.2018.8483168" @default.
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