A model for soil moisture dynamics estimation based on artificial neural network

被引：0
|
作者：
Wang, Wei [1 ,2 ]
Wang, Shuya [3 ]
Chang, Jianxia [1 ]
Bai, Dan [1 ]
机构：
[1] Xian Univ Technol, State Key Lab Base Ecohydraul Engn Arid Area, Sch Water Resources & Hydroelect Engn, Xian 710048, Shaanxi, Peoples R China
[2] Minist Water Resources, Xiaolangdi Project Construct & Management Ctr, Zhengzhou 450000, Henan, Peoples R China
[3] Henan Inst Sci & Technol, Xinxiang 453600, Henan, Peoples R China
来源：
1ST INTERNATIONAL SYMPOSIUM ON WATER RESOURCE AND ENVIRONMENTAL MANAGEMENT (WREM 2018) | 2019年 / 81卷
关键词：
D O I：
10.1051/e3sconf/20198101017
中图分类号：
X [环境科学、安全科学];
学科分类号：
08 ; 0830 ;
摘要：
Research on soil moisture estimation models can effectively improve the growth environment of crops. In this paper, the author studied the artificial neural network and variation pattern of soil moisture. Then, application of the model for water diversion estimation was explored based on artificial neural network. On this basis, an optimization algorithm was presented to simulate water diversion. Furthermore, a model for remote sensing of soil moisture dynamics was applied to artificial neural network. It has been proven that the research can optimize the application of the proposed model, laying a solid foundation for future study.
引用
收藏
页数：5
相关论文
共 50 条
  • [11] An artificial neural network model for soil moisture prediction responding to weather parameters
    Yang Shaohui
    Wang Yiming
    ACTUAL TASKS ON AGRICULTURAL ENGINEERING, PROCEEDINGS, 2006, 34 : 213 - 218
  • [12] Inverse Estimation of Moisture Diffusion Model for Concrete Using Artificial Neural Network
    Lee, Jae Min
    Lee, Chang Joon
    MATERIALS, 2022, 15 (17)
  • [13] Inverting a microwave backscattering model by the use of a neural network for the estimation of soil moisture
    Weimann, A
    IGARSS '98 - 1998 INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, PROCEEDINGS VOLS 1-5: SENSING AND MANAGING THE ENVIRONMENT, 1998, : 1837 - 1839
  • [14] Estimation of soil properties by an artificial neural network
    Ofrikhter, I. V.
    Ponomaryov, A. P.
    Zakharov, A. V.
    Shenkman, R. I.
    MAGAZINE OF CIVIL ENGINEERING, 2022, 110 (02):
  • [15] 60-m Resolution Soil Moisture Estimation Based on a Multisensor Feedforward Neural Network Model
    Portal, Gerard
    Vall-Llossera, Merce
    Lopez-Martinez, Carlos
    Camps, Adriano
    Pablos, Miriam
    Alonso-Gonzalez, Alberto
    Jagdhuber, Thomas
    Irawan, Amir Mustofa
    IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2024, 17 : 15543 - 15566
  • [16] Artificial neural network model for soil moisture forecast in deficit irrigation rice field
    Zhou, MY
    Chen, HW
    Land and Water Management: Decision Tools and Practices, Vols 1 and 2, 2004, : 96 - 100
  • [17] Soil Moisture Content Estimation Based on Sentinel-1 SAR Imagery Using an Artificial Neural Network and Hydrological Components
    Chung, Jeehun
    Lee, Yonggwan
    Kim, Jinuk
    Jung, Chunggil
    Kim, Seongjoon
    REMOTE SENSING, 2022, 14 (03)
  • [18] Neural network soil moisture model for irrigation scheduling
    Gu, Zhe
    Zhu, Tingting
    Jiao, Xiyun
    Xu, Junzeng
    Qi, Zhiming
    COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2021, 180
  • [19] A unified soil thermal conductivity model based on artificial neural network
    Zhang, Nan
    Zou, Haifeng
    Zhang, Limin
    Puppala, Anand J.
    Liu, Songyu
    Cai, Guojun
    INTERNATIONAL JOURNAL OF THERMAL SCIENCES, 2020, 155
  • [20] Prediction Model of Soil Nutrients Loss Based on Artificial Neural Network
    WANG Zhi-liang
    Journal of Northeast Agricultural University(English Edition), 2001, (01) : 37 - 42
12345