[HTML][HTML] Adoption of artificial intelligence in smart cities: A comprehensive review

H Herath, M Mittal - International Journal of Information Management Data …, 2022 - Elsevier
Recently, the population density in cities has increased at a higher pace. According to the
United Nations Population Fund, cities accommodated 3.3 billion people (54%) of the global …

Applications of artificial intelligence in COVID-19 pandemic: A comprehensive review

M Khan, MT Mehran, ZU Haq, Z Ullah, SR Naqvi… - Expert systems with …, 2021 - Elsevier
During the current global public health emergency caused by novel coronavirus disease 19
(COVID-19), researchers and medical experts started working day and night to search for …

On the benefits of using metaheuristics in the hyperparameter tuning of deep learning models for energy load forecasting

N Bacanin, C Stoean, M Zivkovic, M Rakic… - Energies, 2023 - mdpi.com
An effective energy oversight represents a major concern throughout the world, and the
problem has become even more stringent recently. The prediction of energy load and …

[HTML][HTML] Beyond explaining: Opportunities and challenges of XAI-based model improvement

L Weber, S Lapuschkin, A Binder, W Samek - Information Fusion, 2023 - Elsevier
Abstract Explainable Artificial Intelligence (XAI) is an emerging research field bringing
transparency to highly complex and opaque machine learning (ML) models. Despite the …

Time-series production forecasting method based on the integration of Bidirectional Gated Recurrent Unit (Bi-GRU) network and Sparrow Search Algorithm (SSA)

X Li, X Ma, F **ao, C **ao, F Wang, S Zhang - Journal of Petroleum Science …, 2022 - Elsevier
With the gowning demand of improving quality and benefit of unconventional resources,
time-series production prediction plays an increasingly essential role in economic …

Artificial intelligence for COVID-19: a systematic review

L Wang, Y Zhang, D Wang, X Tong, T Liu… - Frontiers in …, 2021 - frontiersin.org
Background: Recently, Coronavirus Disease 2019 (COVID-19), caused by severe acute
respiratory syndrome virus 2 (SARS-CoV-2), has affected more than 200 countries and lead …

Recent applications of machine learning and deep learning models in the prediction, diagnosis, and management of diabetes: a comprehensive review

E Afsaneh, A Sharifdini, H Ghazzaghi… - Diabetology & Metabolic …, 2022 - Springer
Diabetes as a metabolic illness can be characterized by increased amounts of blood
glucose. This abnormal increase can lead to critical detriment to the other organs such as …

Time series predicting of COVID-19 based on deep learning

MO Alassafi, M Jarrah, R Alotaibi - Neurocomputing, 2022 - Elsevier
COVID-19 was declared a global pandemic by the World Health Organisation (WHO) on
11th March 2020. Many researchers have, in the past, attempted to predict a COVID …

[HTML][HTML] Comparative study of machine learning methods for COVID-19 transmission forecasting

A Dairi, F Harrou, A Zeroual, MM Hittawe… - Journal of biomedical …, 2021 - Elsevier
Within the recent pandemic, scientists and clinicians are engaged in seeking new
technology to stop or slow down the COVID-19 pandemic. The benefit of machine learning …

A novel framework for landslide displacement prediction using MT-InSAR and machine learning techniques

C Zhou, Y Cao, L Gan, Y Wang, M Motagh… - Engineering …, 2024 - Elsevier
The prediction of landslide deformation is an important part of landslide early warning
systems. Displacement prediction based on geotechnical in-situ monitoring performs well …