Water Quality Modeling and Prediction Method Based on Sparse Recurrent Neural Network

摘要：

　　It is an important prerequisite for scientific management and maintenance of water resources to accurately predict all kinds of indices that affect water quality.This paper proposed a method of forecasting water quality index and rank based on sparse recurrent neural network(SRNN).The learning algorithm of the network is designed based on the principle of minimum mean square recursive error.A prediction model for predicting water quality index and rank is constructed by using the neural network.The validity of the model is verified by predicting the water quality parameters and water quality rank of a river in Zhejiang Province.

关键词： Water quality modeling Water quality prediction Recurrent neural network

作者: Zhenbo Cheng Zhengyuan Shen Tianqi Zhu Huaidi Lin Leilei Zhang

作者单位: Zhejiang University of Technology,Hangzhou,China

会议类型: 国际会议

会议名称: 2019中国智能自动化大会(CIA,2019)

会议地点: 江苏镇江

会议语种:英文

页码: 736-747

在线出版日期: 2019-09-20（万方平台首次上网日期，不代表论文的发表时间）