Prediction model of dissolved oxygen in marine pasture based on hybrid gray wolf algorithm optimized support vector regression

作     者：Yin, Baoan Wang, Rong Qi, Shengbo Yu, Jingdong Jiang, Wenliang 

作者机构：Ocean Univ China Coll Engn Qingdao 266100 Peoples R China Sencott Intelligent Instrument Co Ltd Qingdao 266100 Peoples R China 

出 版 物：《DESALINATION AND WATER TREATMENT》 (脱盐及水处理)

年 卷 期：2021年第222卷

页      面：156-167页

核心收录：

学科分类：0830[工学-环境科学与工程（可授工学、理学、农学学位）] 0817[工学-化学工程与技术] 08[工学] 0815[工学-水利工程] 

基　　金：National Key Research and Development Project [2016YFC1400800] National Natural Science Foundation of China 

主　　题：Wavelet analysis Gray wolf algorithm Differential evolution algorithm Support vector regression Dissolved oxygen 

摘      要：Water quality prediction plays a vital role in water pollution warning and control. However, traditional prediction models usually suffer from low efficiency and poor robustness. To predict accurately the dissolved oxygen concentration in the marine pasture, a dissolved oxygen prediction model, based on wavelet analysis and hybrid gray wolf algorithm (HGWO) optimized vector regression, was established. Because of the water quality data in the marine pasture is a stationary time series. To improve the accuracy of water quality data, wavelet analysis was applied for data pre-processing in this paper. Besides, after the gray wolf algorithm (GWO) was optimized by the differential evolution algorithm (DE), it was used to optimize the support vector regression (SVR). Hence, the SVR s disadvantages of optimization ability and prediction accuracy both were improved. Back propagation neural network (BPNN), SVR, GWO-SVR, DE-SVR, and this model were, respectively, used to predict the dissolved oxygen concentration of Beidaihe marine pasture. The experimental results show that the mean square error, mean absolute error, and average percentage error of the model are 0.1658, 0.359, and 0.0305, respectively, which are better than the traditional prediction model. So this model has higher prediction accuracy and stronger generalization ability, and it can provide a reference for the precise regulation of aquaculture.