【摘要】 提出了一种基于小波神经网络的智能优化控制系统,并应用到污水处理絮凝过程的优化控制中,采用实验数据进行了测试,同时采用循环抽样验证法来验证系统的测试精度,结果表明该系统可方便有效地进行实时控制,而且控制效果良好,在运行过程中实时控制速度得到明显提高。研究结果表明,小波神经网络所建立的控制模型稳定性好,实时控制速度快,即基于小波神经网络的污水处理絮凝过程控制系统能准确地进行絮凝过程各参数的实时估计,实现污水处理絮凝过程的实时控制。更多还原

【Abstract】 Proposed one kind based on the wavelet neural network’s intelligent optimization control system, and using in the sewage treatment flocculation process’s optimized control, used the empirical datum to carry on the test, simultaneously used the circulation sampling confirmation law to confirm system’s test precision, finally indicated that this system might facilitate carries on the real-time control effectively, moreover the control effect was good, the real-time control speed had the distinct enhancement in the movement pro- cess. The findings indicated the wavelet neural network establishes the control model stability is good, the real-time control speed is quick, namely can carry on flocculation process various parameters accurately based on the wavelet neural network’s sewage treatment flocculation process control system the real-time estimate, realizes the sewage treatment flocculation process real-time control.更多还原