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 …
sustainability of water resources. The literature has shown great potential for nature-inspired …
Reviewing challenges of flood risk management in Malaysia
This study reviewed some of the challenges faced by local authorities in disaster
management, especially flood disasters that occurred in Malaysia. Flood disasters are the …
management, especially flood disasters that occurred in Malaysia. Flood disasters are the …
Fractionation of dyes/salts using loose nanofiltration membranes: Insight from machine learning prediction
Wastewater (WW) served as the crucial indicator for sustainable development, human
health, and the ecosystem. Nanofiltration (NF) membranes are efficient in contaminants, dye …
health, and the ecosystem. Nanofiltration (NF) membranes are efficient in contaminants, dye …
Prediction of meteorological drought and standardized precipitation index based on the random forest (RF), random tree (RT), and Gaussian process regression (GPR …
Agriculture, meteorological, and hydrological drought is a natural hazard which affects
ecosystems in the central India of Maharashtra state. Due to limited historical data for …
ecosystems in the central India of Maharashtra state. Due to limited historical data for …
Streamflow prediction in mountainous region using new machine learning and data preprocessing methods: a case study
Accurate streamflow estimation is crucial for proper water management for irrigation,
hydropower, drinking and industrial purposes. The main aim of this study to adopt new data …
hydropower, drinking and industrial purposes. The main aim of this study to adopt new data …
Predicting streamflow in Peninsular Malaysia using support vector machine and deep learning algorithms
Floods and droughts are environmental phenomena that occur in Peninsular Malaysia due
to extreme values of streamflow (SF). Due to this, the study of SF prediction is highly …
to extreme values of streamflow (SF). Due to this, the study of SF prediction is highly …
[HTML][HTML] An interpretable hybrid deep learning model for flood forecasting based on Transformer and LSTM
W Li, C Liu, Y Xu, C Niu, R Li, M Li, C Hu… - Journal of Hydrology …, 2024 - Elsevier
Study region Flood formation involves complex nonlinear processes and numerous
variables, with data-driven models becoming a key non-engineering approach to flood …
variables, with data-driven models becoming a key non-engineering approach to flood …
A novel hybrid algorithms for groundwater level prediction
Estimating groundwater levels (GWL) with accuracy and reliability, in order to maximize the
use of water resources, it is crucial to reduce water consumption. To predict GWL in the …
use of water resources, it is crucial to reduce water consumption. To predict GWL in the …
Compressive strength of self-compacting concrete modified with rice husk ash and calcium carbide waste modeling: a feasibility of emerging emotional intelligent …
In the present research, the information on compressive strength of self-compacting concrete
(SCC) containing rice husk ash (RHA) and calcium carbide waste (CCW) as an admixture …
(SCC) containing rice husk ash (RHA) and calcium carbide waste (CCW) as an admixture …
Inclusive multiple model using hybrid artificial neural networks for predicting evaporation
Predicting evaporation is essential for managing water resources in basins. Improvement of
the prediction accuracy is essential to identify adequate inputs on evaporation. In this study …
the prediction accuracy is essential to identify adequate inputs on evaporation. In this study …