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 …

Machine learning scopes on microgrid predictive maintenance: Potential frameworks, challenges, and prospects

MY Arafat, MJ Hossain, MM Alam - Renewable and Sustainable Energy …, 2024 - Elsevier
Predictive maintenance is an essential aspect of microgrid operations as it enables
identifying potential equipment failures in advance, reducing downtime, and increasing the …

A multi-model data fusion methodology for reservoir water quality based on machine learning algorithms and bayesian maximum entropy

MG Zamani, MR Nikoo, F Niknazar, G Al-Rawas… - Journal of Cleaner …, 2023 - Elsevier
A major concern in the management of reservoirs is water quality because of the negative
consequences it has on both environment and human life. Artificial Intelligence (AI) concept …

A tree-based stacking ensemble technique with feature selection for network intrusion detection

M Rashid, J Kamruzzaman, T Imam, S Wibowo… - Applied …, 2022 - Springer
Several studies have used machine learning algorithms to develop intrusion systems (IDS),
which differentiate anomalous behaviours from the normal activities of network systems. Due …

A comparative analysis of machine learning algorithms to predict alzheimer's disease

M Bari Antor, AHMS Jamil, M Mamtaz… - Journal of …, 2021 - Wiley Online Library
Alzheimer's disease has been one of the major concerns recently. Around 45 million people
are suffering from this disease. Alzheimer's is a degenerative brain disease with an …

Random forest modeling for network intrusion detection system

N Farnaaz, MA Jabbar - Procedia Computer Science, 2016 - Elsevier
With the growing usage of technology, intrusion detection became an emerging area of
research. Intrusion Detection System (IDS) attempts to identify and notify the activities of …

Ranking the importance of demographic, socioeconomic, and underlying health factors on US COVID-19 deaths: A geographical random forest approach

G Grekousis, Z Feng, I Marakakis, Y Lu, R Wang - Health & Place, 2022 - Elsevier
A growing number of studies show that the uneven spatial distribution of COVID-19 deaths is
related to demographic and socioeconomic disparities across space. However, most studies …

Detection of epileptic seizures on EEG signals using ANFIS classifier, autoencoders and fuzzy entropies

A Shoeibi, N Ghassemi, M Khodatars… - … Signal Processing and …, 2022 - Elsevier
Epileptic seizures are one of the most crucial neurological disorders, and their early
diagnosis will help the clinicians to provide accurate treatment for the patients. The …

Two-way feature extraction for speech emotion recognition using deep learning

A Aggarwal, A Srivastava, A Agarwal, N Chahal… - Sensors, 2022 - mdpi.com
Recognizing human emotions by machines is a complex task. Deep learning models
attempt to automate this process by rendering machines to exhibit learning capabilities …

Cloud-based intrusion detection approach using machine learning techniques

H Attou, A Guezzaz, S Benkirane… - Big Data Mining and …, 2023 - ieeexplore.ieee.org
Cloud computing (CC) is a novel technology that has made it easier to access network and
computer resources on demand such as storage and data management services. In …