New Trends in Mathematical Modeling, Analysis and Optimization for Engineering and Mechanics

Computational modeling has become essential in the engineering field in recent years, providing necessary analyses for real-life problems. Alongside this, optimization techniques have evolved to enhance solutions across diverse problems. Recent advances, including mesh-free methodologies and innovat...

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Huvudupphov: Navas, Pedro, Li, Bo
Materialtyp: Online
Språk:engelska
Utgiven: MDPI - Multidisciplinary Digital Publishing Institute 2026
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Länkar:https://directory.doabooks.org/handle/20.500.12854/170580
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author Navas, Pedro
Li, Bo
author_browse Li, Bo
Navas, Pedro
author_facet Navas, Pedro
Li, Bo
author_sort Navas, Pedro
collection Directory of Open Access Books
description Computational modeling has become essential in the engineering field in recent years, providing necessary analyses for real-life problems. Alongside this, optimization techniques have evolved to enhance solutions across diverse problems. Recent advances, including mesh-free methodologies and innovative finite element approaches, have emerged to complete a powerful range of tools for accurately reproducing engineering mechanical problems. This reprint compiles the accepted articles from the Special Issue of Mathematics (MDPI) titled "New Trends in Mathematical Modeling, Analysis and Optimization for Engineering and Mechanics". It serves as a valuable resource for researchers working on advanced mathematical modeling, numerical methods and optimization techniques in engineering and mechanics.
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spelling doab-20.500.12854ir-1705802026-01-02T16:12:50Z New Trends in Mathematical Modeling, Analysis and Optimization for Engineering and Mechanics Navas, Pedro Li, Bo numerical analysis mesh-free methods boundary value problems numerical optimization computational mechanics data science reinforcement learning Computational modeling has become essential in the engineering field in recent years, providing necessary analyses for real-life problems. Alongside this, optimization techniques have evolved to enhance solutions across diverse problems. Recent advances, including mesh-free methodologies and innovative finite element approaches, have emerged to complete a powerful range of tools for accurately reproducing engineering mechanical problems. This reprint compiles the accepted articles from the Special Issue of Mathematics (MDPI) titled "New Trends in Mathematical Modeling, Analysis and Optimization for Engineering and Mechanics". It serves as a valuable resource for researchers working on advanced mathematical modeling, numerical methods and optimization techniques in engineering and mechanics. 2026-01-02T16:12:47Z 2026-01-02T16:12:47Z 2025 book 978-3-7258-4705-1 https://directory.doabooks.org/handle/20.500.12854/170580 eng application/octet-stream Attribution 4.0 International https://mdpi.com/books https://mdpi.com/books/pdfview/book/11304 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-7258-4706-8 10.3390/books978-3-7258-4706-8 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 978-3-7258-4705-1 178 CH open access
spellingShingle numerical analysis
mesh-free methods
boundary value problems
numerical optimization
computational mechanics
data science
reinforcement learning
Navas, Pedro
Li, Bo
New Trends in Mathematical Modeling, Analysis and Optimization for Engineering and Mechanics
title New Trends in Mathematical Modeling, Analysis and Optimization for Engineering and Mechanics
title_full New Trends in Mathematical Modeling, Analysis and Optimization for Engineering and Mechanics
title_fullStr New Trends in Mathematical Modeling, Analysis and Optimization for Engineering and Mechanics
title_full_unstemmed New Trends in Mathematical Modeling, Analysis and Optimization for Engineering and Mechanics
title_short New Trends in Mathematical Modeling, Analysis and Optimization for Engineering and Mechanics
title_sort new trends in mathematical modeling analysis and optimization for engineering and mechanics
topic numerical analysis
mesh-free methods
boundary value problems
numerical optimization
computational mechanics
data science
reinforcement learning
topic_facet numerical analysis
mesh-free methods
boundary value problems
numerical optimization
computational mechanics
data science
reinforcement learning
url https://directory.doabooks.org/handle/20.500.12854/170580
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