基于神经网络和人工蜂群算法的污水处理水质预测模型研究

Water Quality Prediction Model of Wastewater Treatment based on Neural Network and Artificial Bee Colony Algorithm

随着社会飞速发展,污水处理效率亟待提高。而由于低端设备精度低以及效率不高,高端设备难以普及的问题,导致污水处理效率不高。通过数学模型对污水处理的出水水质预测是弥补设备问题的有效解决途径。通过设计一个基于神经网络的预测模型,保证其预测的精准度,更快速准确的提供污水处理后的出水水质主要参数的预测,并在此基础上通过引进人工蜂群算法来进一步提高其收敛速度,提高本预测模型的效率。

With the rapid development of society, wastewater treatment efficiency needs to be improved. Due to the low - end equipment, and efficiency is not high, high - end equipment is difficult to spread, so the sewage treat- ment efficiency is not high. Through mathematical model to predict the sewage treatment effluent is an effective rem- edy equipment problems solution. Therefore, by designing a predictive model based on neural network, the accura- cy of its predictions can be ensured, and treated wastewater effluent quality forecasting main parameters can be provided quickly and accurately. And on this basis, through the introduction of artificial bee colony algorithm, the convergence rate and improve the efficiency of the prediction model can be further improved.