[HTML][HTML] Groundwater level prediction using machine learning models: A comprehensive review

H Tao, MM Hameed, HA Marhoon… - Neurocomputing, 2022 - Elsevier
Developing accurate soft computing methods for groundwater level (GWL) forecasting is
essential for enhancing the planning and management of water resources. Over the past two …

Hybridized artificial intelligence models with nature-inspired algorithms for river flow modeling: A comprehensive review, assessment, and possible future research …

H Tao, SI Abba, AM Al-Areeq, F Tangang… - … Applications of Artificial …, 2024 - Elsevier
River flow (Q flow) is a hydrological process that considerably impacts the management and
sustainability of water resources. The literature has shown great potential for nature-inspired …

Nutcracker optimizer: A novel nature-inspired metaheuristic algorithm for global optimization and engineering design problems

M Abdel-Basset, R Mohamed, M Jameel… - Knowledge-Based …, 2023 - Elsevier
This work presents a novel nature-inspired metaheuristic called Nutcracker Optimization
Algorithm (NOA) inspired by Clark's nutcrackers. The nutcrackers exhibit two distinct …

Improving streamflow prediction using a new hybrid ELM model combined with hybrid particle swarm optimization and grey wolf optimization

RM Adnan, RR Mostafa, O Kisi, ZM Yaseen… - Knowledge-Based …, 2021 - Elsevier
Accurate runoff estimation is crucial for optimal reservoir operation and irrigation purposes.
In this study, a novel hybrid method is proposed for monthly runoff prediction in Mangla …

Mutation based improved dragonfly optimization algorithm for a neuro-fuzzy system in short term wind speed forecasting

H Parmaksiz, U Yuzgec, E Dokur, N Erdogan - Knowledge-based systems, 2023 - Elsevier
The Dragonfly algorithm (DA) is a heuristic optimization algorithm that is commonly used for
complex optimization problems. Despite its widespread application, the abundance of social …

[HTML][HTML] A visualized hybrid intelligent model to delineate Swedish fine-grained soil layers using clay sensitivity

A Ghaderi, AA Shahri, S Larsson - Catena, 2022 - Elsevier
In the current paper, a hybrid model was developed to generate 3D delineated soil horizons
using clay sensitivity (S t) with 1 m depth intervals in a landslide prone area in the southwest …

Pre-and post-dam river water temperature alteration prediction using advanced machine learning models

DK Vishwakarma, R Ali, SA Bhat, A Elbeltagi… - … Science and Pollution …, 2022 - Springer
Dams significantly impact river hydrology by changing the timing, size, and frequency of low
and high flows, resulting in a hydrologic regime that differs significantly from the natural flow …

Application of innovative machine learning techniques for long-term rainfall prediction

S Markuna, P Kumar, R Ali, DK Vishwkarma… - Pure and Applied …, 2023 - Springer
Rainfall forecasting is critical because it is the componen t that has the strongest link to
natural disasters such as landslides, floods, mass movements, and avalanches. The present …

Computational assessment of groundwater salinity distribution within coastal multi-aquifers of Bangladesh

M Jamei, M Karbasi, A Malik, L Abualigah… - Scientific Reports, 2022 - nature.com
The rising salinity trend in the country's coastal groundwater has reached an alarming rate
due to unplanned use of groundwater in agriculture and seawater seeping into the …

Optimized ANFIS model using hybrid metaheuristic algorithms for Parkinson's disease prediction in IoT environment

IM El-Hasnony, SI Barakat, RR Mostafa - IEEE Access, 2020 - ieeexplore.ieee.org
Throughout recent years, the progress of telemonitoring and telediagnostics devices for
evaluating and tracking Parkinson's (PD) disease has become increasingly important. The …