Description
Advances in Structural Engineering—Optimization, 1st ed. 2021
Emerging Trends in Structural Optimization
Studies in Systems, Decision and Control Series, Vol. 326
Coordinators: Nigdeli Sinan Melih, Bekdaş Gebrail, Kayabekir Aylin Ece, Yucel Melda
Language: EnglishSubject for Advances in Structural Engineering—Optimization:
Keywords
Algorithms; Artificial Intelligence; Artificial Neural Networks; Evolutionary Algorithms; Genetic Algorithms; Harmony Search; Hybrid Algorithms; Optimization; Optimum Design; Metaheuristic Algorithms; Bioinspired Algorithms; Swarm Intelligence; Structural Engineering; Nature-inspired Algorithms; Machine Learning; Optimum Structural Control
Publication date: 12-2021
310 p. · 15.5x23.5 cm · Paperback
Publication date: 12-2020
310 p. · 15.5x23.5 cm · Hardback
Description
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This book is an up-to-date source for computation applications of optimization, prediction via artificial intelligence methods, and evaluation of metaheuristic algorithm with different structural applications. As the current interest of researcher, metaheuristic algorithms are a high interest topic area since advance and non-optimized problems via mathematical methods are challenged by the development of advance and modified algorithms. The artificial intelligence (AI) area is also important in predicting optimum results by skipping long iterative optimization processes. The machine learning used in generation of AI models also needs optimum results of metaheuristic-based approaches.
This book is a great source to researcher, graduate students, and bachelor students who gain project about structural optimization. Differently from the academic use, the chapter that emphasizes different scopes and methods can take the interest and help engineer working in design and production of structural engineering projects.
Summarizes the latest developments in optimization and metaheuristic algorithms with emphasis on applications in structural engineering
Presents artificial intelligence and machine learning methods to predict optimum results by skipping long optimization processes
Introduces the fundamentals of the metaheuristic methods, their implementations, and applications so that undergraduates and graduates in engineering can gain good understanding of materials and contents