Analysis, characterization, prediction, and attribution of extreme atmospheric events with machine learning and deep learning techniques: a review
Atmospheric extreme events cause severe damage to human societies and ecosystems.
The frequency and intensity of extremes and other associated events are continuously …
The frequency and intensity of extremes and other associated events are continuously …
A new benchmark on machine learning methodologies for hydrological processes modelling: a comprehensive review for limitations and future research directions
ZM Yaseen - Knowledge-Based Engineering …, 2023 - … journals.publicknowledgeproject.org
The best practice of watershed management is through the understanding of the
hydrological processes. As a matter of fact, hydrological processes are highly associated …
hydrological processes. As a matter of fact, hydrological processes are highly associated …
[HTML][HTML] A novel approach based on integration of convolutional neural networks and echo state network for daily electricity demand prediction
Predicting electricity demand data is considered an essential task in decisions taking, and
establishing new infrastructure in the power generation network. To deliver a high-quality …
establishing new infrastructure in the power generation network. To deliver a high-quality …
[HTML][HTML] Two-step deep learning framework with error compensation technique for short-term, half-hourly electricity price forecasting
Prediction of electricity price is crucial for national electricity markets supporting sale prices,
bidding strategies, electricity dispatch, control and market volatility management. High …
bidding strategies, electricity dispatch, control and market volatility management. High …
[HTML][HTML] Efficient daily electricity demand prediction with hybrid deep-learning multi-algorithm approach
Predicting electricity demand (G) is crucial for electricity grid operation and management. In
order to make reliable predictions, model inputs must be analyzed for predictive features …
order to make reliable predictions, model inputs must be analyzed for predictive features …
Electricity demand error corrections with attention bi-directional neural networks
Reliable forecast of electricity demand is crucial to stability, supply, and management of
electricity grids. Short-term hourly and sub-hourly demand forecasts are difficult due to the …
electricity grids. Short-term hourly and sub-hourly demand forecasts are difficult due to the …
[HTML][HTML] Deep learning ensembles for accurate fog-related low-visibility events forecasting
In this paper we propose and discuss different Deep Learning-based ensemble algorithms
for a problem of low-visibility events prediction due to fog. Specifically, seven different Deep …
for a problem of low-visibility events prediction due to fog. Specifically, seven different Deep …
Cloud computing load prediction by decomposition reinforced attention long short-term memory network optimized by modified particle swarm optimization algorithm
Computer resources provision over the internet resulted in the wide spread usage of cloud
computing paradigm. With the use of such resources come certain challenges that can …
computing paradigm. With the use of such resources come certain challenges that can …
[HTML][HTML] Explainable deeply-fused nets electricity demand prediction model: Factoring climate predictors for accuracy and deeper insights with probabilistic confidence …
Electricity consumption has stochastic variabilities driven by the energy market volatility. The
capability to predict electricity demand that captures stochastic variances and uncertainties …
capability to predict electricity demand that captures stochastic variances and uncertainties …
[HTML][HTML] Efficient prediction of fog-related low-visibility events with Machine Learning and evolutionary algorithms
Low visibility events are a severe problem for road transport, causing accidents and major
economic losses. Their accurate prediction may help prevent these problems. For that …
economic losses. Their accurate prediction may help prevent these problems. For that …