Water Quality Prediction in the Waste Water Treatment Process Based on Ridge Regression Echo State Network

2018 2nd International Conference on Artificial Intelligence Applications and Technologies

计算机科学

Zhao, Jing^1,2 ; Zhao, Chao^1,2 ; Zhang, Fan^1,2 ; Wu, Gang^1,2 ; Wang, Haitao^1,2

China National Institute of Standardization, Beijing

100191, China^1

AQSIQ Key Laboratory of Human Factors and Ergonomics(CNIS), Beijing

100191, China^2

关键词: Echo state networks;    Ill posed problem;    Moore-Penrose inverse;    Ridge regression;    Ridge-regression algorithm;    Water quality predictions;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/435/1/012025/pdf
DOI  :  10.1088/1757-899X/435/1/012025

学科分类：计算机科学（综合）

来源: IOP

【 摘 要 】

Echo state network (ESN), a novel recurrent neural network, has a randomly and sparsely connected reservoir. Since the output weights are computed by Moore-Penrose inverse, the ill-posed problem may exist in the ESN. To overcome this problem, ridge regression echo state network (RESN) is proposed, in which the ridge regression algorithm is used to calculate the output weights instead of linear regression. Simulation results show that the RESN has better performance than some other existing methods, thus can deal with the ill-posed problem.