Short-term rainfall forecasting using machine learning-based approaches of PSO-SVR, LSTM and CNN
Short-term rainfall forecasting plays an important role in hydrologic modeling and water
resource management problems such as flood warning and real time control of urban …
resource management problems such as flood warning and real time control of urban …
Improving multiple model ensemble predictions of daily precipitation and temperature through machine learning techniques
Abstract Multi-Model Ensembles (MMEs) are used for improving the performance of GCM
simulations. This study evaluates the performance of MMEs of precipitation, maximum …
simulations. This study evaluates the performance of MMEs of precipitation, maximum …
A review of the application of hybrid machine learning models to improve rainfall prediction
Rainfall is one of the most important meteorological phenomena that impacts many fields,
including agriculture, energy, water resources management, and mining, among others …
including agriculture, energy, water resources management, and mining, among others …
[HTML][HTML] Study on the spatiotemporal dynamic of ground-level ozone concentrations on multiple scales across China during the blue sky protection campaign
Abstract Surface ozone (O 3), one of the harmful air pollutants, generated significantly
negative effects on human health and plants. Existing O 3 datasets with coarse …
negative effects on human health and plants. Existing O 3 datasets with coarse …
Determinants of learning management systems during COVID-19 pandemic for sustainable education
Research has shown that effective and efficient learning management systems (LMS) were
the main reasons for sustainable education in developed nations during COVID-19 …
the main reasons for sustainable education in developed nations during COVID-19 …
Artificial intelligence based ensemble model for prediction of vehicular traffic noise
Vehicular traffic noise is the main source of noise pollution in major cities around the globe.
A reliable and accurate method for the estimation of vehicular traffic noise is therefore …
A reliable and accurate method for the estimation of vehicular traffic noise is therefore …
Groundwater prediction using machine-learning tools
Predicting groundwater availability is important to water sustainability and drought
mitigation. Machine-learning tools have the potential to improve groundwater prediction …
mitigation. Machine-learning tools have the potential to improve groundwater prediction …
Rainfall prediction using machine learning models: literature survey
Research on rainfall prediction contributes to different fields that have a huge impact on our
daily life. With the advancement of computer technology, machine learning has been …
daily life. With the advancement of computer technology, machine learning has been …
Hybrid machine learning ensemble techniques for modeling dissolved oxygen concentration
The reliable prediction of dissolved oxygen concentration (DO) is significantly crucial for
protecting the health of the aquatic ecosystem. The current research employed four different …
protecting the health of the aquatic ecosystem. The current research employed four different …
Comparative implementation between neuro-emotional genetic algorithm and novel ensemble computing techniques for modelling dissolved oxygen concentration
Accurate prediction of dissolved oxygen (DO) concentration is important for managing
healthy aquatic ecosystems. This study investigates the comparative potential of the …
healthy aquatic ecosystems. This study investigates the comparative potential of the …