Combining autoregressive integrated moving average with Long Short-Term Memory neural network and optimisation algorithms for predicting ground water level

ZS Khozani, FB Banadkooki, M Ehteram… - Journal of Cleaner …, 2022 - Elsevier
The groundwater resources are the essential sources for irrigation and agriculture
management. Forecasting groundwater levels (GWL) for the current and future periods is an …

Review of artificial intelligence and internet of things technologies in land and water management research during 1991–2021: A bibliometric analysis

A Patel, A Kethavath, NL Kushwaha, A Naorem… - … Applications of Artificial …, 2023 - Elsevier
The challenges of urbanization, land degradation, water scarcity, and climate change are
threatening agricultural systems and food security. Therefore, it is essential to manage land …

Short-term streamflow forecasting using hybrid deep learning model based on grey wolf algorithm for hydrological time series

HC Kilinc, A Yurtsever - Sustainability, 2022 - mdpi.com
The effects of developing technology and rapid population growth on the environment have
been expanding gradually. Particularly, the growth in water consumption has revealed the …

Drought forecasting using new advanced ensemble-based models of reduced error pruning tree

M Shahdad, B Saber - Acta Geophysica, 2022 - Springer
The present study investigates the prediction accuracy of standalone Reduced Error Pruning
Tree model and its integration with Bagging (BA), Dagging (DA), Additive Regression (AR) …

Influence of hydrological state on trophic state in dam induced seasonally inundated flood plain wetland

P Singha, S Pal - Ecohydrology & Hydrobiology, 2023 - Elsevier
A Good many research works focused on investigating wetland habitat state and trophic
state (TS) but as far the knowledge is concerned, very little attention was paid to the …

Monthly streamflow prediction using hybrid extreme learning machine optimized by bat algorithm: a case study of Cheliff watershed, Algeria

S Difi, Y Elmeddahi, A Hebal, VP Singh… - Hydrological …, 2023 - Taylor & Francis
In the present paper, we propose a new approach for monthly streamflow prediction based
on the extreme learning machine (ELM) and the metaheuristic bat algorithm (Bat-ELM). The …

Prediction of Irrigation Water Quality Indices Using Random Committee, Discretization Regression, REPTree, and Additive Regression

M Al-Mukhtar, A Srivastava, L Khadke… - Water Resources …, 2024 - Springer
This study aims to evaluate the performance of four ensemble machine learning methods, ie,
Random Committee, Discretization Regression, Reduced Error Pruning Tree, and Additive …

Daily river flow simulation using ensemble disjoint aggregating M5-Prime model

K Khosravi, N Attar, SM Bateni, C Jun, D Kim… - Heliyon, 2024 - cell.com
Accurate prediction of daily river flow (Q t) is a challenging task in hydrological modeling,
particularly vital for flood mitigation and water resource management. This study introduces …

[PDF][PDF] Enhanced forecasting of multi-step ahead daily soil temperature using advanced hybrid vote algorithm-based tree models

J Hatamiafkoueieh, S Heddam… - Journal of …, 2023 - iwaponline.com
In this study, the vote algorithm used to improve the performances of three machine-learning
models including M5Prime (M5P), random forest (RF), and random tree (RT) is developed …

Comparative assessment of advanced machine learning techniques for simulation of lake water level fluctuations based on different dimensionality reduction methods

M Riazi, M Karimi, S Eslamian… - Earth Science Informatics, 2023 - Springer
Global warming and unprecedented human impacts causing environmental degradation are
taking place at an alarming rate. As one of the most valuable and important water resources …