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Water agricultural management based on hydrology using machine learning techniques for feature extraction and classification

  • Research Article - Hydrology and Hydraulics
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Abstract

For irrigation in agriculture, water is a natural resource. Recycling water use is vital for the sustainable development of ecological environment and for resource conservation. Different substances that are thought to be pollutants and contribute to the deterioration of water quality are present in the wastewater from daily life and industrial activity. This research propose novel method in agricultural water management using feature extraction as well as classification based on DL methods. Inputs are collected as agriculture field water management as well as processed for noise removal, normalization and smoothening. Processed input data features are extracted utilizing kernel convolutional component analysis network. The extracted features has been classified using Quadratic reinforcement NN. Experimental analysis are carried out in terms of accuracy, precision, recall, positive predictive value, RMSE and mAP. Proposed technique attained accuracy of 92%, precision of 86%, recall of 65%, positive predictive value of 71%, RMSE of 55%, MAP of 51%.

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Acknowledgements

The researchers would like to acknowledge Deanship of Scientific Research, Taif University for funding this work.

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Authors and Affiliations

  1. School of Innovation and Entrepreneurship, Sanming University, No. 25 Jingdong Road, Sanming City, 365004, Fujian, China

    Yi-Chia Lin

  2. Department of Information System, Faculty of Computing and Information Technology, King Abdulaziz University, City Rabigh, Saudi Arabia

    Almuhannad Sulaiman Alorfi

  3. Department of Information Systems, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia

    Tawfiq Hasanin

  4. Center for Transdisciplinary Research, Saveetha Dental College, Saveetha Institute of Medical and Technical Science, Chennai, India

    Mahendran Arumugam

  5. Department of Computer Science, College of Computers and Information Technology, Taif University, P. O. Box 11099, Taif, 21944, Saudi Arabia

    Roobaea Alroobaea, Majed Alsafyani & Wael Y. Alghamdi

Authors
  1. Yi-Chia Lin
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  2. Almuhannad Sulaiman Alorfi
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  3. Tawfiq Hasanin
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  4. Mahendran Arumugam
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  5. Roobaea Alroobaea
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  6. Majed Alsafyani
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  7. Wael Y. Alghamdi
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Corresponding author

Correspondence to Yi-Chia Lin.

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This article does not contain any studies with animals performed by any of the authors.

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Informed consent was obtained from all individual participants included in the study.

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Edited by Prof. Antonio Zuorro (GUEST EDITOR) / Dr. Michael Nones (CO-EDITOR-IN-CHIEF).

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Lin, YC., Alorfi, A.S., Hasanin, T. et al. Water agricultural management based on hydrology using machine learning techniques for feature extraction and classification. Acta Geophys. 72, 1945–1955 (2024). https://doi.org/10.1007/s11600-023-01082-9

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  • DOI: https://doi.org/10.1007/s11600-023-01082-9

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