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

• Autorzy: Lin Yi-Chia , Alorfi Almuhannad Sulaiman , Hasanin Tawfiq , Arumugam Mahendran , Alroobaea Roobaea , Alsafyani Majed , Alghamdi Wael Y.

Identyfikatory

DOI

10.1007/s11600-023-01082-9

• Języki publikacji: EN

Abstrakty

EN

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%.

Słowa kluczowe

EN

water management; feature extraction; classification; deep learning; agricultural field

PL

zarządzanie wodą; ekstrakcja cech; klasyfikacja; głębokie uczenie; pole uprawne

• Wydawca: Instytut Geofizyki PAN ; Springer
• Czasopismo: Acta Geophysica
• Rocznik: 2024
• Tom: Vol. 72, no. 3
• Strony: 1945--1955
• Opis fizyczny: Bibliogr. 21 poz.

Twórcy

autor

Lin Yi-Chia

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

autor

Alorfi Almuhannad Sulaiman

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

autor

Hasanin Tawfiq

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

autor

Arumugam Mahendran

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

autor

Alroobaea Roobaea

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

autor

Alsafyani Majed

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

autor

Alghamdi Wael Y.

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

Bibliografia

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