The potential of a novel support vector machine trained with modified mayfly optimization algorithm for streamflow prediction
This paper focuses on the development of a robust accurate streamflow prediction model by
balancing the abilities of exploitation and exploration to find the best parameters of a …
balancing the abilities of exploitation and exploration to find the best parameters of a …
Application of machine learning techniques to model a full-scale wastewater treatment plant with biological nutrient removal
MS Zaghloul, G Achari - Journal of Environmental Chemical Engineering, 2022 - Elsevier
A full-scale biological nutrient removal wastewater treatment process was simulated using
artificial intelligence. In wastewater treatment plants, adaptive machine learning models can …
artificial intelligence. In wastewater treatment plants, adaptive machine learning models can …
A framework based on multivariate distribution-based virtual sample generation and DNN for predicting water quality with small data
A El Bilali, H Lamane, A Taleb, A Nafii - Journal of Cleaner Production, 2022 - Elsevier
Abstract Deep Neural Network (DNN) is a powerful tool for predicting and monitoring water
quality. However, its application is only limited to well-monitored zones where the availability …
quality. However, its application is only limited to well-monitored zones where the availability …
Development of integrative data intelligence models for thermo-economic performances prediction of hybrid organic rankine plants
Computer aid models such as machine learning (ML) are massively observed to be
successfully applied in different engineering-related domains. The current research was …
successfully applied in different engineering-related domains. The current research was …
Earth skin temperature long-term prediction using novel extended Kalman filter integrated with Artificial Intelligence models and information gain feature selection
Predictions of Earth skin temperature (EST) can provide essential information for diverse
engineering applications such as energy harvesting and agriculture activities. Several …
engineering applications such as energy harvesting and agriculture activities. Several …
Interpretation the influence of hydrometeorological variables on soil temperature prediction using the potential of deep learning model
S Elsayed, M Gupta… - Knowledge …, 2023 - … journals.publicknowledgeproject.org
The importance of soil temperature (ST) quantification can contribute to diverse ecological
modelling processes as well as for agricultural activities. Over the literature, it was evident …
modelling processes as well as for agricultural activities. Over the literature, it was evident …
An overview of streamflow prediction using random forest algorithm
Since the first application of Artificial Intelligence in the field of hydrology, there has been a
great deal of interest in exploring aspects of future enhancements to hydrology. This is …
great deal of interest in exploring aspects of future enhancements to hydrology. This is …
[HTML][HTML] Multi-regional modeling of cumulative COVID-19 cases integrated with environmental forest knowledge estimation: A deep learning ensemble approach
Reliable modeling of novel commutative cases of COVID-19 (CCC) is essential for
determining hospitalization needs and providing the benchmark for health-related policies …
determining hospitalization needs and providing the benchmark for health-related policies …
Hybrid and Integrative Evolutionary Machine Learning in Hydrology: A Systematic Review and Meta-analysis
A Mahdavi-Meymand, W Sulisz… - … Methods in Engineering, 2024 - Springer
It has been claimed throughout the last two decades that hydrological machine learning
(ML) models may produce more accurate and resilient simulations than previous …
(ML) models may produce more accurate and resilient simulations than previous …
An efficient strategy for predicting river dissolved oxygen concentration: Application of deep recurrent neural network model
Dissolved oxygen (DO) concentration in water is one of the key parameters for assessing
river water quality. Artificial intelligence (AI) methods have previously proved to be accurate …
river water quality. Artificial intelligence (AI) methods have previously proved to be accurate …