[HTML][HTML] The latest innovative avenues for the utilization of artificial Intelligence and big data analytics in water resource management
The effective management of water resources is essential to environmental stewardship and
sustainable development. Traditional approaches to water resource management (WRM) …
sustainable development. Traditional approaches to water resource management (WRM) …
A review of hybrid deep learning applications for streamflow forecasting
Deep learning has emerged as a powerful tool for streamflow forecasting and its
applications have garnered significant interest in the hydrological community. Despite the …
applications have garnered significant interest in the hydrological community. Despite the …
Neuroforecasting of daily streamflows in the UK for short-and medium-term horizons: A novel insight
Predicting streamflows, which is crucial for flood defence and optimal management of water
resources for drinking, irrigation, hydropower generation and ecosystem conservation, is a …
resources for drinking, irrigation, hydropower generation and ecosystem conservation, is a …
Hybridized artificial intelligence models with nature-inspired algorithms for river flow modeling: A comprehensive review, assessment, and possible future research …
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 …
Application of machine learning in water resources management: A systematic literature review
In accordance with the rapid proliferation of machine learning (ML) and data management,
ML applications have evolved to encompass all engineering disciplines. Owing to the …
ML applications have evolved to encompass all engineering disciplines. Owing to the …
Predicting lake water quality index with sensitivity-uncertainty analysis using deep learning algorithms
Regular monitoring and assessment of water quality is essential to maintain the quality of
lake water. A commonly used method for assessing water quality is the Water Quality Index …
lake water. A commonly used method for assessing water quality is the Water Quality Index …
Robust runoff prediction with explainable artificial intelligence and meteorological variables from deep learning ensemble model
J Wu, Z Wang, J Dong, X Cui, S Tao… - Water Resources …, 2023 - Wiley Online Library
Accurate runoff forecasting plays a vital role in issuing timely flood warnings. Whereas,
previous research has primarily focused on historical runoff and precipitation variability …
previous research has primarily focused on historical runoff and precipitation variability …
Comparative evaluation of LSTM, CNN, and ConvLSTM for hourly short-term streamflow forecasting using deep learning approaches
This study investigates the effectiveness of three deep learning methods, Long Short-Term
Memory (LSTM), Convolutional Neural Network (CNN), and Convolutional Long Short-Term …
Memory (LSTM), Convolutional Neural Network (CNN), and Convolutional Long Short-Term …
A state-of-art-review on machine-learning based methods for PV
In the current era, Artificial Intelligence (AI) is becoming increasingly pervasive with
applications in several applicative fields effectively changing our daily life. In this scenario …
applications in several applicative fields effectively changing our daily life. In this scenario …
Metaheuristic evolutionary deep learning model based on temporal convolutional network, improved aquila optimizer and random forest for rainfall-runoff simulation …
X Qiao, T Peng, N Sun, C Zhang, Q Liu, Y Zhang… - Expert Systems with …, 2023 - Elsevier
Accurate and reliable runoff prediction is of great significance to water resources
management, disaster monitoring and rational development and utilization of water …
management, disaster monitoring and rational development and utilization of water …