THE PREDICTION MODEL OF WATER QUALITY ON THE BP ARTIFICIAL NEURAL NETWORK

被引:0
|
作者
Yan, Cheng-Ming [1 ]
机构
[1] Guangdong Polytech Water Resources & Elect Engn, Guangzhou, Guangdong, Peoples R China
关键词
Water quality; BP; Artificial neural network; ANN; The forecast model;
D O I
暂无
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
BP neural network can achieve arbitrary nonlinear mapping of the input to the output, so it is extensively adopted in intelligent control, image recognition, hydrological predicting and water-resource quantity evaluation, etc., has stronger features of mapping, classification, functional fitting. This paper chooses the water quality of Lanzhou section of Yellow river as example by use of BP model to forecast the water quality. It is well verified that BP network model can reach the purposes of early warning and predicting.
引用
收藏
页码:250 / 256
页数:7
相关论文
共 50 条
  • [21] The Water Productivity Forecasting Based on BP Neural Network and Gray Prediction Model
    Xie Jing
    Han Huiling
    CIVIL ENGINEERING IN CHINA - CURRENT PRACTICE AND RESEARCH REPORT, 2010, : 939 - 943
  • [22] Prediction of yarn quality based on BP neural network
    Yuan, Jing
    Li, Yinglin
    Chen, Suying
    ADVANCES IN TEXTILE ENGINEERING, 2011, 331 : 449 - +
  • [23] ARTIFICIAL NEURAL NETWORK MODEL FOR WATER CONSUMPTION PREDICTION IN DAIRY FARMS
    Osaki, Marcia Regina
    Palhares, Julio Cesar Pascale
    Aguiar, Fernando Guimaraes
    BIOSCIENCE JOURNAL, 2024, 40
  • [24] ARTIFICIAL NEURAL NETWORK PREDICTION MODEL OF KARST WATER IN COAL MINES
    Huang, Pinghua
    Wang, Xinyi
    Han, Sumin
    FRESENIUS ENVIRONMENTAL BULLETIN, 2019, 28 (01): : 452 - 458
  • [25] Using water quality parameters to prediction of the ion-based trihalomethane by an artificial neural network model
    Ali Akbar Babaei
    Yaser Tahmasebi Birgani
    Zeynab Baboli
    Heydar Maleki
    Kambiz Ahmadi Angali
    Environmental Monitoring and Assessment, 2023, 195
  • [26] Using water quality parameters to prediction of the ion-based trihalomethane by an artificial neural network model
    Babaei, Ali Akbar
    Tahmasebi Birgani, Yaser
    Baboli, Zeynab
    Maleki, Heydar
    Ahmadi Angali, Kambiz
    ENVIRONMENTAL MONITORING AND ASSESSMENT, 2023, 195 (08)
  • [27] An Artificial Neural Network Model for Water Quality Prediction in the Amoju Hydrographic Subbasin, Cajamarca-Peru
    Llanos, Alex Alfredo Huaman
    Meza, Jeimis Royler Yalta
    Cordova, Danicza Violeta Sanchez
    Martinez, Juan Carlos Chasquero
    Huatangari, Lenin Quiñones
    Sanchez, Dulcet Lorena Quinto
    Segura, Roxana Rojas
    Gutierrez, Alfredo Lazaro Ludeña
    International Journal of Advanced Computer Science and Applications, 2024, 15 (09) : 1021 - 1032
  • [28] A quick prediction of hardness from water quality parameters by artificial neural network
    Roy, Ritabrata
    Majumder, Mrinmoy
    INTERNATIONAL JOURNAL OF ENVIRONMENT AND SUSTAINABLE DEVELOPMENT, 2018, 17 (2-3) : 247 - 257
  • [29] Water Environmental Quality Assessment and Effect Prediction Based on Artificial Neural Network
    An, Wentian
    3D IMAGING-MULTIDIMENSIONAL SIGNAL PROCESSING AND DEEP LEARNING, VOL 1, 2022, 297 : 91 - 100
  • [30] Prediction of water quality index (WQI) based on artificial neural network (ANN)
    Khuan, LY
    Hamzah, N
    Jailani, R
    2002 STUDENT CONFERENCE ON RESEARCH AND DEVELOPMENT, PROCEEDINGS: GLOBALIZING RESEARCH AND DEVELOPMENT IN ELECTRICAL AND ELECTRONICS ENGINEERING, 2002, : 157 - 161