Aquatic ecosystem-based water management in agriculture project by data analytics using classification by deep learning techniques

• Autorzy: Anuradha Tadiparthi , Sen Sanjay Kumar , Tamilarasi Kathirvel Murugan , Haleem Sulaima Lebbe Abdul , Abdul-Samad Zulkiflee , Anupong Wongchai

Identyfikatory

DOI

10.1007/s11600-023-01104-6

• Języki publikacji: EN

Abstrakty

EN

Over the past few decades, irrigation using groundwater has increased significantly. It has significant effects on local to regional climates as well as terrestrial energy fluxes, food production, and water availability. High cost of metering equipment installation as well as maintenance, privacy concerns, and existence of unregistered or illegal wells make it difficult to monitor irrigation water use on a large scale. This study suggests a unique approach to DL-based feature extraction and categorization for ecosystem-based water management in agricultural fields. Agriculture field water analysis data were used as the input in this instance, which was subsequently processed for noise removal, smoothing, and normalisation. Particle swarm-based convolutional architecture has been used to extract the processed data feature. Back regressive propagation based on incentive Q-learning is used to classify the extracted features. Experimental analysis has been carried out in terms of accuracy, precision, recall, F-1 score, RMSE and mAPE. Proposed technique obtained accuracy of 92%, precision of 78%, recall of 83%, F_1 score of 76%, RMSE of 55% and MAPE of 57%.

Słowa kluczowe

EN

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

PL

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

• Wydawca: Instytut Geofizyki PAN ; Springer
• Czasopismo: Acta Geophysica
• Rocznik: 2024
• Tom: Vol. 72, no. 3
• Strony: 2059--2069
• Opis fizyczny: Bibliogr. 21 poz.

Twórcy

autor

Anuradha Tadiparthi

• Department of Information Technology, VR Siddhartha Engineering College, Vijayawada, Andhra Pradesh, India

autor

Sen Sanjay Kumar

• Department of Information Technology, Vardhaman College of Engineering (Autonomous), Hyderabad, India

autor

Tamilarasi Kathirvel Murugan

• School of Computer Science and Engineering, VIT University, Chennai Campus, Chennai, India

autor

Haleem Sulaima Lebbe Abdul

• Department of Information and Communication Technology, Faculty of Technology, South Eastern University of Sri Lanka, Oluvil, Sri Lanka

autor

Abdul-Samad Zulkiflee

• Department of Quantity Surveying, Faculty of Built Environment, University of Malaya, 50603 Kuala Lumpur, Malaysia

autor

Anupong Wongchai

• Chiang Mai, Thailand

Bibliografia

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