Advanced Computational Methods for Modeling, Prediction and Optimization—A Review

This paper provides a comprehensive review of recent advancements in computational methods for modeling, simulation, and optimization of complex systems in materials engineering, mechanical engineering, and energy systems. We identified key trends and highlighted the integration of artificial intell...

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Vydané v:Materials Ročník 17; číslo 14; s. 3521
Hlavní autori: Krzywanski, Jaroslaw, Sosnowski, Marcin, Grabowska, Karolina, Zylka, Anna, Lasek, Lukasz, Kijo-Kleczkowska, Agnieszka
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Switzerland MDPI AG 16.07.2024
Predmet:
Algorithms
Artificial intelligence
Cloud computing
Complex systems
Engineering
Machine learning
Material properties
Materials engineering
Mathematical models
Mechanical engineering
Monte Carlo simulation
Neural networks
Numerical analysis
Optimization
Optimization techniques
State-of-the-art reviews
System theory
Systems analysis
Trends
complex systems
modeling
optimization
simulation
energy systems
machine learning
material engineering
artificial intelligence
ISSN:1996-1944, 1996-1944
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Popis
Shrnutí:This paper provides a comprehensive review of recent advancements in computational methods for modeling, simulation, and optimization of complex systems in materials engineering, mechanical engineering, and energy systems. We identified key trends and highlighted the integration of artificial intelligence (AI) with traditional computational methods. Some of the cited works were previously published within the topic: “Computational Methods: Modeling, Simulations, and Optimization of Complex Systems”; thus, this article compiles the latest reports from this field. The work presents various contemporary applications of advanced computational algorithms, including AI methods. It also introduces proposals for novel strategies in materials production and optimization methods within the energy systems domain. It is essential to optimize the properties of materials used in energy. Our findings demonstrate significant improvements in accuracy and efficiency, offering valuable insights for researchers and practitioners. This review contributes to the field by synthesizing state-of-the-art developments and suggesting directions for future research, underscoring the critical role of these methods in advancing engineering and technological solutions.
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ISSN:1996-1944
1996-1944
DOI:10.3390/ma17143521