Hybrid Metaheuristics in Structural Engineering: Including Machine Learning Applications

Bekdas, Gebrail (Editor)/ Nigdeli, Sinan Melih (Editor)

ISBN 10: 3031347277 / ISBN 13: 9783031347276

Editore: Springer Nature, 2023

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313 pages. 9.25x6.10x0.79 inches. In Stock.

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Dati bibliografici

• Titolo: Hybrid Metaheuristics in Structural Engineering: Including Machine Learning Applications
• Editore: Springer Nature
• Data di pubblicazione: 2023
• Lingua: Inglese
• ISBN 10: 3031347277
• ISBN 13: 9783031347276
• Rilegatura: Hardcover
• Condizione: Brand New
• Peso: 0,68 chilogrammi

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Riassunto

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.