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 …
Stacked machine learning algorithms and bidirectional long short-term memory networks for multi-step ahead streamflow forecasting: A comparative study
Prediction of river flow rates is an essential task for both flood protection and optimal water
resource management. The high uncertainty associated with basin characteristics …
resource management. The high uncertainty associated with basin characteristics …
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 …
Drought indicator analysis and forecasting using data driven models: case study in Jaisalmer, India
Agricultural droughts are a prime concern for economies worldwide as they negatively
impact the productivity of rain-fed crops, employment, and income per capita. In this study …
impact the productivity of rain-fed crops, employment, and income per capita. In this study …
Exploring temporal dynamics of river discharge using univariate long short-term memory (LSTM) recurrent neural network at East Branch of Delaware River
River flow prediction is a pivotal task in the field of water resource management during the
era of rapid climate change. The highly dynamic and evolving nature of the climatic …
era of rapid climate change. The highly dynamic and evolving nature of the climatic …
Short-term forecasts of streamflow in the UK based on a novel hybrid artificial intelligence algorithm
In recent years, the growing impact of climate change on surface water bodies has made the
analysis and forecasting of streamflow rates essential for proper planning and management …
analysis and forecasting of streamflow rates essential for proper planning and management …
Metaheuristic approaches for prediction of water quality indices with relief algorithm-based feature selection
Monitoring and assessing groundwater quality are important for sustainable water resource
management. Therefore, the present study aimed to analyze and predict the water quality …
management. Therefore, the present study aimed to analyze and predict the water quality …
Comparative assessment of improved SVM method under different kernel functions for predicting multi-scale drought index
This paper focus on the drought monitoring and forecasting for semi-arid region based on
the various machine learning models and SPI index. Drought phenomena are crucial role in …
the various machine learning models and SPI index. Drought phenomena are crucial role in …
Evaluation of data-driven hybrid machine learning algorithms for modelling daily reference evapotranspiration
Reference evapotranspiration (ET0) is one of the crucial variables used for irrigation
scheduling, agricultural production, and water balance studies. This study compares six …
scheduling, agricultural production, and water balance studies. This study compares six …
[HTML][HTML] Vulnerability of the rip current phenomenon in marine environments using machine learning models
Hidden and perilous rip currents are one of the primary factors leading to drownings of
beach swimmers. By identifying the coastal areas with the highest likelihood of generating …
beach swimmers. By identifying the coastal areas with the highest likelihood of generating …