Application of artificial intelligence in geotechnical engineering: A state-of-the-art review

A Baghbani, T Choudhury, S Costa, J Reiner - Earth-Science Reviews, 2022 - Elsevier
Geotechnical engineering deals with soils and rocks and their use in engineering
constructions. By their nature, soils and rocks exhibit complex behaviours and a high level of …

Modeling, diagnostics, optimization, and control of internal combustion engines via modern machine learning techniques: A review and future directions

M Aliramezani, CR Koch, M Shahbakhti - Progress in Energy and …, 2022 - Elsevier
A critical review of the existing Internal Combustion Engine (ICE) modeling, optimization,
diagnosis, and control challenges and the promising state-of-the-art Machine Learning (ML) …

Review of artificial intelligence applications in engineering design perspective

N Yüksel, HR Börklü, HK Sezer, OE Canyurt - Engineering Applications of …, 2023 - Elsevier
Having passed the primitive phases and starting to revolutionize many different fields in
some way, artificial intelligence is on its way to becoming a disruptive technology. It is also …

Genetic algorithms: Theory, genetic operators, solutions, and applications

B Alhijawi, A Awajan - Evolutionary Intelligence, 2024 - Springer
A genetic algorithm (GA) is an evolutionary algorithm inspired by the natural selection and
biological processes of reproduction of the fittest individual. GA is one of the most popular …

Tailoring microcombs with inverse-designed, meta-dispersion microresonators

E Lucas, SP Yu, TC Briles, DR Carlson, SB Papp - Nature Photonics, 2023 - nature.com
Nonlinear wave mixing in optical microresonators offers new perspectives to generate
compact optical-frequency microcombs, which enable an ever-growing number of …

A physics-informed deep learning paradigm for car-following models

Z Mo, R Shi, X Di - Transportation research part C: emerging technologies, 2021 - Elsevier
Car-following behavior has been extensively studied using physics-based models, such as
Intelligent Driving Model (IDM). These models successfully interpret traffic phenomena …

[HTML][HTML] Enhancing property prediction and process optimization in building materials through machine learning: A review

K Stergiou, C Ntakolia, P Varytis, E Koumoulos… - Computational Materials …, 2023 - Elsevier
Abstract Analysis and design, as the most critical components in material science, require a
highly rigorous approach to assure long-term success. Due to a recent increase in the …

Artificial intelligence enabled project management: a systematic literature review

I Taboada, A Daneshpajouh, N Toledo, T de Vass - Applied Sciences, 2023 - mdpi.com
In the Industry 5.0 era, companies are leveraging the potential of cutting-edge technologies
such as artificial intelligence for more efficient and green human-centric production. In a …

Optimization Enabled Deep Learning‐Based DDoS Attack Detection in Cloud Computing

S Balasubramaniam, C Vijesh Joe… - … Journal of Intelligent …, 2023 - Wiley Online Library
Cloud computing is a vast revolution in information technology (IT) that inhibits scalable and
virtualized sources to end users with low infrastructure cost and maintenance. They also …

Learning path personalization and recommendation methods: A survey of the state-of-the-art

AH Nabizadeh, JP Leal, HN Rafsanjani… - Expert Systems with …, 2020 - Elsevier
A learning path is the implementation of a curriculum design. It consists of a set of learning
activities that help users achieve particular learning goals. Personalizing these paths …