[HTML][HTML] A systematic review of fourth industrial revolution technologies in smart irrigation: constraints, opportunities, and future prospects for sub-Saharan Africa

J Wanyama, E Bwambale, S Kiraga, A Katimbo… - Smart Agricultural …, 2024 - Elsevier
Abstract The adoption of Fourth Industrial Revolution (4IR) technologies has revolutionized
agricultural practices worldwide. However, their application in the context of sub-Saharan …

[HTML][HTML] Towards efficient irrigation management at field scale using new technologies: A systematic literature review

A Bounajra, K El Guemmat, K Mansouri… - Agricultural Water …, 2024 - Elsevier
Life on earth is linked to water resources. Recently, alarm bells have been ringing in global
organizations to raise awareness of the importance of rational use of water resources, which …

Enhanced multi-step streamflow series forecasting using hybrid signal decomposition and optimized reservoir computing models

JHK Larcher, SF Stefenon, L dos Santos Coelho… - Expert Systems with …, 2024 - Elsevier
This study evaluates the use of different time series decomposition methods in association
with echo state networks (ESNs), deep echo state networks (DeepESNs), and next …

TPE-CatBoost: An adaptive model for soil moisture spatial estimation in the main maize-producing areas of China with multiple environment covariates

J Yu, W Zheng, L Xu, F Meng, J Li, L Zhangzhong - Journal of Hydrology, 2022 - Elsevier
Maize is one of the major crops in China. The soil water content (SWC) in the root zone of
maize is a critical indicator that guides agricultural production decisions and can affect …

[HTML][HTML] Fostering deep learning approaches to evaluate the impact of urbanization on vegetation and future prospects

Z Zafar, MS Mehmood, Z Shiyan, M Zubair, M Sajjad… - Ecological …, 2023 - Elsevier
Vegetation is an essential component of our global ecosystem and an important indicator of
the dynamics and productivity of land cover. Vegetation forecasting research has been …

[HTML][HTML] Smart reference evapotranspiration using Internet of Things and hybrid ensemble machine learning approach

RN Bashir, M Saeed, M Al-Sarem, R Marie, M Faheem… - Internet of Things, 2023 - Elsevier
Reference Evapotranspiration (ET o) is the cornerstone of efficient water utilization for
sustainability in agriculture. The standard Penman–Montieth (PM) approach of Reference …

Quantitative prediction model and prewarning system of water yield capacity (WYC) from coal seam roof based on deep learning and joint advanced detection

F Dong, H Yin, W Cheng, C Zhang, D Zhang, H Ding… - Energy, 2024 - Elsevier
As one of the most abundant fossil fuels in the world, the safe and efficient mining of coal
resources has greatly affects all fields of human production and life. Accurate prediction of …

IoT-driven machine learning for precision viticulture optimization

C Pero, S Bakshi, M Nappi… - IEEE Journal of Selected …, 2023 - ieeexplore.ieee.org
Precision agriculture (PA), also known as smart farming, has emerged as an innovative
solution to address contemporary challenges in agricultural sustainability. A particular sector …

Machine‐learning based multi‐layer soil moisture forecasts—An application case study of the Montana 2017 flash drought

J Du, JS Kimball, K Jencso, Z Hoylman… - Water Resources …, 2024 - Wiley Online Library
Soil moisture (SM) is an essential climate variable, governing land‐atmosphere interactions,
runoff generation, and vegetation growth and productivity. Timely forecasts of SM spatial …

Quantification of soil water content by machine learning using enhanced high-resolution ERT

F Meng, J Wang, Y Zhao, Z Chen - Journal of Hydrology, 2024 - Elsevier
The accurate acquisition of soil water content is a fundamental cornerstone of research into
hydrological processes and agricultural engineering. Electrical Resistivity Tomography …