[HTML][HTML] Deep learning based computer vision approaches for smart agricultural applications

VG Dhanya, A Subeesh, NL Kushwaha… - Artificial Intelligence in …, 2022 - Elsevier
The agriculture industry is undergoing a rapid digital transformation and is growing powerful
by the pillars of cutting-edge approaches like artificial intelligence and allied technologies …

A comprehensive survey on aquila optimizer

B Sasmal, AG Hussien, A Das, KG Dhal - Archives of Computational …, 2023 - Springer
Aquila Optimizer (AO) is a well-known nature-inspired optimization algorithm (NIOA) that
was created in 2021 based on the prey grabbing behavior of Aquila. AO is a population …

Prediction of weighted arithmetic water quality index for urban water quality using ensemble machine learning model

U Mohseni, CB Pande, SC Pal, F Alshehri - Chemosphere, 2024 - Elsevier
Urban water quality index (WQI) is an important factor for assessment quality of groundwater
in the urban and rural area. In this research, the Weighted Arithmetic Water Quality Index …

Metaheuristic approaches for prediction of water quality indices with relief algorithm-based feature selection

NL Kushwaha, J Rajput, T Suna, DR Sena… - Ecological …, 2023 - Elsevier
Monitoring and assessing groundwater quality are important for sustainable water resource
management. Therefore, the present study aimed to analyze and predict the water quality …

Using unsupervised machine learning models to drive groundwater chemistry and associated health risks in Indo-Bangla Sundarban region

JN Jannat, ARMT Islam, MY Mia, SC Pal, T Biswas… - Chemosphere, 2024 - Elsevier
Groundwater is an essential resource in the Sundarban regions of India and Bangladesh,
but its quality is deteriorating due to anthropogenic impacts. However, the integrated factors …

Ant-inspired metaheuristic algorithms for combinatorial optimization problems in water resources management

R Bhavya, L Elango - Water, 2023 - mdpi.com
Ant-inspired metaheuristic algorithms known as ant colony optimization (ACO) offer an
approach that has the ability to solve complex problems in both discrete and continuous …

Revolutionizing groundwater management with hybrid AI models: A practical review

M Zaresefat, R Derakhshani - Water, 2023 - mdpi.com
Develo** precise soft computing methods for groundwater management, which includes
quality and quantity, is crucial for improving water resources planning and management. In …

Groundwater quality characterization using an integrated water quality index and multivariate statistical techniques

VK Gautam, M Kothari, B Al-Ramadan, PK Singh… - PLoS one, 2024 - journals.plos.org
This study attempts to characterize and interpret the groundwater quality (GWQ) using a GIS
environment and multivariate statistical approach (MSA) for the Jakham River Basin (JRB) in …

Development of wavelet-based kalman online sequential extreme learning machine optimized with boruta-random forest for drought index forecasting

M Jamei, I Ahmadianfar, M Karbasi, A Malik… - … Applications of Artificial …, 2023 - Elsevier
Drought is a stochastic and recurring hydrological natural hazard that occurs due to a
shortage of precipitation over a period of time. Drought forecasting in water resources …

[HTML][HTML] Development of an enhanced bidirectional recurrent neural network combined with time-varying filter-based empirical mode decomposition to forecast weekly …

M Karbasi, M Jamei, M Ali, A Malik, X Chu… - Agricultural water …, 2023 - Elsevier
Evapotranspiration is one of agricultural water management's most significant and impactful
hydrologic processes. A new multi-decomposition deep learning-based technique is …