A one-dimensional BOD-DO coupling model for water quality simulation is presented, which adopts Streeter-Phelps equations and the theory of back-propagation artificial neural network. The water quality data of Yangtze...A one-dimensional BOD-DO coupling model for water quality simulation is presented, which adopts Streeter-Phelps equations and the theory of back-propagation artificial neural network. The water quality data of Yangtze River in the Chongqing region in the year of 1989 are divided into 5 groups and used in the learning and testing courses of this model. The result shows that such model is feasible for water quality simulation and is more accurate than traditional models.展开更多
针对污水处理厂生化池中参数监测智能化水平不高、人力耗费较大的问题,提出基于麻雀算法-长短期记忆神经网络(Sparrow Search Algorithm-Long Short Term Memory Network,SSA-LSTM)的水质参数预测模型。以污水处理过程中好氧区溶解氧(Di...针对污水处理厂生化池中参数监测智能化水平不高、人力耗费较大的问题,提出基于麻雀算法-长短期记忆神经网络(Sparrow Search Algorithm-Long Short Term Memory Network,SSA-LSTM)的水质参数预测模型。以污水处理过程中好氧区溶解氧(Dissolved Oxygen,DO)、好氧区混合液悬浮固体(Mixed Liquid Suspended Solids,MLSS)质量浓度、缺氧区DO、缺氧区氧化还原电位(Oxidation-Reduction Potential,ORP)、厌氧区DO和厌氧区ORP 6个关键指标为数据样本,进行实例研究。将SSA-LSTM的预测结果与长短期记忆神经网络(Long Short-Term Memory Network,LSTM)、粒子群算法(Particle Swarm optimization-Long Short Term Memory Network,PSO-LSTM)、深度森林以及支持向量机进行对比分析,结果显示:SSA-LSTM在6个参数上的均方误差(EMSE)和决定系数(R2)均表现出更好的预测性,预测精度最高。展开更多
基金Funded by the National Natural Science Foundation of China (No.59838300 No.59778021)
文摘A one-dimensional BOD-DO coupling model for water quality simulation is presented, which adopts Streeter-Phelps equations and the theory of back-propagation artificial neural network. The water quality data of Yangtze River in the Chongqing region in the year of 1989 are divided into 5 groups and used in the learning and testing courses of this model. The result shows that such model is feasible for water quality simulation and is more accurate than traditional models.
