A review of modern machine learning techniques in the prediction of remaining useful life of lithium-ion batteries
P Sharma, BJ Bora - Batteries, 2022 - mdpi.com
The intense increase in air pollution caused by vehicular emissions is one of the main
causes of changing weather patterns and deteriorating health conditions. Furthermore …
causes of changing weather patterns and deteriorating health conditions. Furthermore …
A comprehensive survey on higher order neural networks and evolutionary optimization learning algorithms in financial time series forecasting
The financial market volatility has been a focus of study for experts over past decades. While
stockbrokers and investors expect reliable projections of future stock indices, it instead …
stockbrokers and investors expect reliable projections of future stock indices, it instead …
Forecasting building energy consumption: Adaptive long-short term memory neural networks driven by genetic algorithm
The real-world building can be regarded as a comprehensive energy engineering system;
its actual energy consumption depends on complex affecting factors, including various …
its actual energy consumption depends on complex affecting factors, including various …
Federated learning with hyperparameter-based clustering for electrical load forecasting
Electrical load prediction has become an integral part of power system operation. Deep
learning models have found popularity for this purpose. However, to achieve a desired …
learning models have found popularity for this purpose. However, to achieve a desired …
[HTML][HTML] Introducing the Open Energy Ontology: Enhancing data interpretation and interfacing in energy systems analysis
Heterogeneous data, different definitions and incompatible models are a huge problem in
many domains, with no exception for the field of energy systems analysis. Hence, it is hard to …
many domains, with no exception for the field of energy systems analysis. Hence, it is hard to …
A hybrid intelligent genetic algorithm for truss optimization based on deep neutral network
J Liu, Y **a - Swarm and Evolutionary Computation, 2022 - Elsevier
The truss optimization problem has been extensively investigated, and the optimized trusses
have been widely used in various fields. Truss optimization is a challenging optimization …
have been widely used in various fields. Truss optimization is a challenging optimization …
Explaining household electricity consumption using quantile regression, decision tree and artificial neural network
Electricity as an energy carrier par excellence has a vital role in economic development.
However, even with the transformation of power systems that follows technological …
However, even with the transformation of power systems that follows technological …
Influential aspects on melting and solidification of PCM energy storage containers in building envelope applications
Phase change materials (PCMs) incorporated building envelope for thermal energy storage
(TES) considerably enhances building thermal energy and improves indoor comfort …
(TES) considerably enhances building thermal energy and improves indoor comfort …
[HTML][HTML] Prediction of sorption enhanced steam methane reforming products from machine learning based soft-sensor models
Carbon dioxide-abated hydrogen can be synthesised via various processes, one of which is
sorption enhanced steam methane reforming (SE-SMR), which produces separated streams …
sorption enhanced steam methane reforming (SE-SMR), which produces separated streams …
Short-term electricity load forecasting based on a novel data preprocessing system and data reconstruction strategy
Y Meng, S Yun, Z Zhao, J Guo, X Li, D Ye, L Jia… - Journal of Building …, 2023 - Elsevier
Accurate forecasting of the electricity load plays a crucial role in the decision-making and
operation of the smart grid. The characteristics of load series such as non-stationarity, non …
operation of the smart grid. The characteristics of load series such as non-stationarity, non …