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- Leidėjas: Walter de Gruyter
- Metai: 2026
- Puslapiai: 236
- ISBN-10: 3119145661
- ISBN-13: 9783119145664
- Formatas: 17.6 x 24.2 x 2.3 cm, kieti viršeliai
- Kalba: Anglų
- Extra -25 % nuolaida šiai knygai su kodu: ENG25
Computational Mathematics in Engineering (el. knyga) (skaityta knyga) | knygos.lt
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Aprašymas
The monograph represents peer-reviewed original studies that make significant contributions to various branches of Computational Mathematics and Engineering. Each chapter highlights current trends in its respective research field and offers valuable insights, innovative methodologies, and recent advances in theories and computational applications. Key topics include artificial neural networks, data sciences, fuzzy set theory, numerical optimization techniques, soft computing, computational fluid dynamics and mathematical modelling. Additionally, several AI and machine learning algorithms are included, showcasing noteworthy computational results. This monograph features mathematical content validated by simulation results, enhancing the significance of the book. It serves as a valuable resource for both early-career and experienced researchers tackling complex real-world problems, such as addressing COVID-19 dynamics and solving transportation issues in engineering designs that traditional methods fail to resolve.
EXTRA 25 % nuolaida su kodu: ENG25
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- Leidėjas: Walter de Gruyter
- Metai: 2026
- Puslapiai: 236
- ISBN-10: 3119145661
- ISBN-13: 9783119145664
- Formatas: 17.6 x 24.2 x 2.3 cm, kieti viršeliai
- Kalba: Anglų
The monograph represents peer-reviewed original studies that make significant contributions to various branches of Computational Mathematics and Engineering. Each chapter highlights current trends in its respective research field and offers valuable insights, innovative methodologies, and recent advances in theories and computational applications. Key topics include artificial neural networks, data sciences, fuzzy set theory, numerical optimization techniques, soft computing, computational fluid dynamics and mathematical modelling. Additionally, several AI and machine learning algorithms are included, showcasing noteworthy computational results. This monograph features mathematical content validated by simulation results, enhancing the significance of the book. It serves as a valuable resource for both early-career and experienced researchers tackling complex real-world problems, such as addressing COVID-19 dynamics and solving transportation issues in engineering designs that traditional methods fail to resolve.
Atsiliepimai