Machine Learning, Deep Learning and Statistical Analysis for forecasting building energy consumption—A systematic review

M Khalil, AS McGough, Z Pourmirza… - … Applications of Artificial …, 2022‏ - Elsevier
The building sector accounts for 36% of the total global energy usage and 40% of
associated Carbon Dioxide emissions. Therefore, the forecasting of building energy …

Artificial neural networks for photonic applications—from algorithms to implementation: tutorial

P Freire, E Manuylovich, JE Prilepsky… - Advances in Optics and …, 2023‏ - opg.optica.org
This tutorial–review on applications of artificial neural networks in photonics targets a broad
audience, ranging from optical research and engineering communities to computer science …

Hyperparameter tuning for machine learning algorithms used for arabic sentiment analysis

E Elgeldawi, A Sayed, AR Galal, AM Zaki - Informatics, 2021‏ - mdpi.com
Machine learning models are used today to solve problems within a broad span of
disciplines. If the proper hyperparameter tuning of a machine learning classifier is …

BIM-supported automatic energy performance analysis for green building design using explainable machine learning and multi-objective optimization

Y Shen, Y Pan - Applied Energy, 2023‏ - Elsevier
Supported by the combination of the advanced BIM technique with intelligent algorithms, this
paper develops a systematic framework using explainable machine learning and multi …

A novel stacked generalization ensemble-based hybrid LGBM-XGB-MLP model for Short-Term Load Forecasting

M Massaoudi, SS Refaat, I Chihi, M Trabelsi… - Energy, 2021‏ - Elsevier
This paper proposes an effective computing framework for Short-Term Load Forecasting
(STLF). The proposed technique copes with the stochastic variations of the load demand …

Advances in solar forecasting: Computer vision with deep learning

Q Paletta, G Terrén-Serrano, Y Nie, B Li… - Advances in Applied …, 2023‏ - Elsevier
Renewable energy forecasting is crucial for integrating variable energy sources into the grid.
It allows power systems to address the intermittency of the energy supply at different …

A novel MRI diagnosis method for brain tumor classification based on CNN and Bayesian Optimization

M Ait Amou, K **a, S Kamhi, M Mouhafid - Healthcare, 2022‏ - mdpi.com
Brain tumor is one of the most aggressive diseases nowadays, resulting in a very short life
span if it is diagnosed at an advanced stage. The treatment planning phase is thus essential …

Multi-objective optimization for energy-efficient building design considering urban heat island effects

Y Zhang, BK Teoh, L Zhang - Applied Energy, 2024‏ - Elsevier
Building energy performance (BEP) associated with climate change and urban heat island
effects (UHI) play an important role in urban sustainable development. To predict and …

[HTML][HTML] The role of machine learning and design of experiments in the advancement of biomaterial and tissue engineering research

G Al-Kharusi, NJ Dunne, S Little, TJ Levingstone - Bioengineering, 2022‏ - mdpi.com
Optimisation of tissue engineering (TE) processes requires models that can identify
relationships between the parameters to be optimised and predict structural and …

Multivariate stacked bidirectional long short term memory for lithium-ion battery health management

RR Ardeshiri, M Liu, C Ma - Reliability Engineering & System Safety, 2022‏ - Elsevier
Prognostics and health management (PHM) will ensure the safe and reliable operation of
the battery systems. The remaining useful life (RUL) prediction as one of the major PHM …