A survey on deep learning methods for power load and renewable energy forecasting in smart microgrids
Microgrids have recently emerged as a building block for smart grids combining distributed
renewable energy sources (RESs), energy storage devices, and load management …
renewable energy sources (RESs), energy storage devices, and load management …
The state of the art in deep learning applications, challenges, and future prospects: A comprehensive review of flood forecasting and management
Floods are a devastating natural calamity that may seriously harm both infrastructure and
people. Accurate flood forecasts and control are essential to lessen these effects and …
people. Accurate flood forecasts and control are essential to lessen these effects and …
Covid-19 outbreak prediction with machine learning
Several outbreak prediction models for COVID-19 are being used by officials around the
world to make informed decisions and enforce relevant control measures. Among the …
world to make informed decisions and enforce relevant control measures. Among the …
Applications of artificial intelligence for disaster management
Natural hazards have the potential to cause catastrophic damage and significant
socioeconomic loss. The actual damage and loss observed in the recent decades has …
socioeconomic loss. The actual damage and loss observed in the recent decades has …
Flood prediction using machine learning models: Literature review
Floods are among the most destructive natural disasters, which are highly complex to model.
The research on the advancement of flood prediction models contributed to risk reduction …
The research on the advancement of flood prediction models contributed to risk reduction …
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 …
Are we preparing for a good AI society? A bibliometric review and research agenda
Artificial intelligence (AI) may be one of the most disruptive technologies of the 21st century,
with the potential to transform every aspect of society. Preparing for a “good AI society” has …
with the potential to transform every aspect of society. Preparing for a “good AI society” has …
An enhanced extreme learning machine model for river flow forecasting: State-of-the-art, practical applications in water resource engineering area and future research …
Despite the massive diversity in the modeling requirements for practical hydrological
applications, there remains a need to develop more reliable and intelligent expert systems …
applications, there remains a need to develop more reliable and intelligent expert systems …
State of the art of machine learning models in energy systems, a systematic review
Machine learning (ML) models have been widely used in the modeling, design and
prediction in energy systems. During the past two decades, there has been a dramatic …
prediction in energy systems. During the past two decades, there has been a dramatic …
Evaluation of CatBoost method for prediction of reference evapotranspiration in humid regions
Accurate estimation of reference evapotranspiration (ET 0) is critical for water resource
management and irrigation scheduling. This study evaluated the potential of a new machine …
management and irrigation scheduling. This study evaluated the potential of a new machine …