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Hybrid Metaheuristics in Structural Engineering: Including Machine Learning Applications 2023 ed. [Kõva köide]

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  • Formaat: Hardback, 305 pages, kõrgus x laius: 235x155 mm, kaal: 698 g, 84 Illustrations, color; 48 Illustrations, black and white; VIII, 305 p. 132 illus., 84 illus. in color., 1 Hardback
  • Sari: Studies in Systems, Decision and Control 480
  • Ilmumisaeg: 16-Jun-2023
  • Kirjastus: Springer International Publishing AG
  • ISBN-10: 3031347277
  • ISBN-13: 9783031347276
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  • Kõva köide
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  • Formaat: Hardback, 305 pages, kõrgus x laius: 235x155 mm, kaal: 698 g, 84 Illustrations, color; 48 Illustrations, black and white; VIII, 305 p. 132 illus., 84 illus. in color., 1 Hardback
  • Sari: Studies in Systems, Decision and Control 480
  • Ilmumisaeg: 16-Jun-2023
  • Kirjastus: Springer International Publishing AG
  • ISBN-10: 3031347277
  • ISBN-13: 9783031347276
Teised raamatud teemal:
From the start of life, people used their brains to make something better in design in ordinary works. Due to that, metaheuristics are essential to living things, and several inspirations from life have been used in the generation of new algorithms. These algorithms have unique features, but the usage of different features of different algorithms may give more effective optimum results in means of precision in optimum results, computational effort, and convergence.    

This book is a timely book to summarize the latest developments in the optimization of structural engineering systems covering all classical approaches and new trends including hybrids metaheuristic algorithms. Also, artificial intelligence and machine learning methods are included to predict optimum results by skipping long optimization processes. The main objective of this book is to introduce the fundamentals and current development of methods and their applications in structural engineering. 





 
Introduction and Overview: Hybrid Metaheuristics in Structural
Engineering - Including Machine Learning Applications.- The Development of
Hybrid Metaheuristics in Structural Engineering.-  Optimum Design of
Reinforced Concrete Columns in Case of Fire.- Hybrid Social Network Search
and Material Generation Algorithm for Shape and Size Optimization of Truss
Structures.- Development of a Hybrid Algorithm for Optimum Design of a
Large-Scale Truss Structure.