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 …

A comprehensive survey on higher order neural networks and evolutionary optimization learning algorithms in financial time series forecasting

S Behera, SC Nayak, AVSP Kumar - Archives of Computational Methods …, 2023 - Springer
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 …

Forecasting building energy consumption: Adaptive long-short term memory neural networks driven by genetic algorithm

XJ Luo, LO Oyedele - Advanced Engineering Informatics, 2021 - Elsevier
The real-world building can be regarded as a comprehensive energy engineering system;
its actual energy consumption depends on complex affecting factors, including various …

Federated learning with hyperparameter-based clustering for electrical load forecasting

N Gholizadeh, P Musilek - Internet of Things, 2022 - Elsevier
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 …

[HTML][HTML] Introducing the Open Energy Ontology: Enhancing data interpretation and interfacing in energy systems analysis

M Booshehri, L Emele, S Flügel, H Förster, J Frey… - Energy and AI, 2021 - Elsevier
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 …

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 …

Explaining household electricity consumption using quantile regression, decision tree and artificial neural network

JC Nsangou, J Kenfack, U Nzotcha, PSN Ekam… - Energy, 2022 - Elsevier
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 …

Enhancing multi-scenario data-driven energy consumption prediction in campus buildings by selecting appropriate inputs and improving algorithms with attention …

C Zhang, Z Luo, Y Rezgui, T Zhao - Energy and Buildings, 2024 - Elsevier
Effective building energy prediction is vital for sustainable development, especially with an
increasing focus on flexibility and elasticity in building energy usage. However, challenges …

[HTML][HTML] Investigating the effect of new and old weather data on the energy consumption of buildings affected by global warming in different climates

AM Reveshti, A Ebrahimpour, J Razmara - International Journal of …, 2023 - Elsevier
Energy assessments and studies for the coming years in buildings show that the effects of
climate change, particularly the problem of global warming, play an important role in …

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 …