Machine learning-based potential loss assessment of maize and rice production due to flash flood in Himachal Pradesh, India DOI
Swadhina Koley, Soora Naresh Kumar

Environmental Monitoring and Assessment, Journal Year: 2024, Volume and Issue: 196(6)

Published: May 2, 2024

Language: Английский

Assessment of Advanced Machine and Deep Learning Approaches for Predicting CO2 Emissions from Agricultural Lands: Insights Across Diverse Agroclimatic Zones DOI Creative Commons
Endre Harsányi, Morad Mirzaei, Sana Arshad

et al.

Earth Systems and Environment, Journal Year: 2024, Volume and Issue: 8(4), P. 1109 - 1125

Published: July 3, 2024

Abstract Prediction of carbon dioxide (CO 2 ) emissions from agricultural soil is vital for efficient and strategic mitigating practices achieving climate smart agriculture. This study aimed to evaluate the ability two machine learning algorithms [gradient boosting regression (GBR), support vector (SVR)], deep [feedforward neural network (FNN) convolutional (CNN)] in predicting CO Maize fields agroclimatic regions i.e., continental (Debrecen-Hungary), semi-arid (Karaj-Iran). research developed three scenarios . Each scenario by a combination between input variables [i.e., temperature (Δ), moisture (θ), date measurement (SD), management (SM)] SC1: (SM + Δ θ), SC2: Δ), SC3: θ)]. Results showed that average emission Debrecen was 138.78 ± 72.04 ppm ( n = 36), while Karaj 478.98 174.22 36). Performance evaluation results train set revealed high prediction accuracy achieved GBR SC1 with highest R 0.8778, lowest root mean squared error (RMSE) 72.05, followed SC3. Overall, performance MDLM ranked as > FNN CNN SVR. In testing phase, 0.918, RMSE 67.75, SC3, (R 0.887, 79.881). The GRB findings provide insights into strategies, enabling stakeholders work towards more sustainable climate-resilient future

Language: Английский

Citations

7
Digital technologies for water use and management in agriculture: Recent applications and future outlook DOI Creative Commons
Carlos Parra-López, Saker Ben Abdallah, Guillermo Garcia‐Garcia

et al.

Agricultural Water Management, Journal Year: 2025, Volume and Issue: 309, P. 109347 - 109347

Published: Feb. 2, 2025

Language: Английский

Citations

0
Predictive Modeling of soil salinity integrating remote sensing and soil variables: An ensembled deep learning approach DOI Creative Commons
Sana Arshad, Syed Jamil Hasan Kazmi, Endre Harsányi

et al.

Energy Nexus, Journal Year: 2025, Volume and Issue: unknown, P. 100374 - 100374

Published: Feb. 1, 2025

Language: Английский

Citations

0
Predicting Agricultural Drought in Central Europe by Using Machine Learning Algorithms DOI Creative Commons
Endre Harsányi

Journal of Agriculture and Food Research, Journal Year: 2025, Volume and Issue: unknown, P. 101783 - 101783

Published: March 1, 2025

Language: Английский

Citations

0
Irrigation Water Quality Prognostication: An Innovative Ensemble Architecture Leveraging Deep Learning and Machine Learning for Enhanced SAR and ESP Estimation in the East Coast of India DOI
Alok Kumar Pati, Alok Ranjan Tripathy, Debabrata Nandi

et al.

Journal of environmental chemical engineering, Journal Year: 2025, Volume and Issue: unknown, P. 116433 - 116433

Published: April 1, 2025

Language: Английский

Citations

0
Prediction of Urban Surface Water Quality Scenarios Using Water Quality Index (WQI), Multivariate Techniques, and Machine Learning (ML) Models in Water Resources, in Baitarani River Basin, Odisha: Potential Benefits and Associated Challenges DOI
Abhijeet Das

Earth Systems and Environment, Journal Year: 2025, Volume and Issue: unknown

Published: April 9, 2025

Language: Английский

Citations

0
Groundwater quality assessment for irrigation in coastal region (Güzelyurt), Northern Cyprus and importance of empirical model for predicting groundwater quality (electric conductivity) DOI Creative Commons
Hüseyin Gökçekuş, Youssef Kassem,

Temel Rızza

et al.

Environmental Earth Sciences, Journal Year: 2025, Volume and Issue: 84(8)

Published: April 1, 2025

Language: Английский

Citations

0
Design of real-time hybrid nanofiltration/reverse osmosis seawater desalination plant performance based on deep learning application DOI
Fahad Jibrin Abdu, Sani I. Abba, Jamilu Usman

et al.

Desalination, Journal Year: 2025, Volume and Issue: unknown, P. 118918 - 118918

Published: April 1, 2025

Language: Английский

Citations

0
Evaluating machine learning performance in predicting sodium adsorption ratio for sustainable soil-water management in the eastern Mediterranean DOI Creative Commons
Safwan Mohammed, Sana Arshad, Bashar Bashir

et al.

Journal of Environmental Management, Journal Year: 2024, Volume and Issue: 370, P. 122640 - 122640

Published: Sept. 27, 2024

Language: Английский

Citations

3
Dynamics of land cover/land use with heat islands phenomenon and its ecological evaluation using remote sensing data (1992–2022) DOI

Noreena,

Muhammad Farhan Ul Moazzam, Muhammad S. Jamil

et al.

Environment Development and Sustainability, Journal Year: 2025, Volume and Issue: unknown

Published: May 6, 2025

Language: Английский

Citations

0