Hybrid metaheuristics in structural engineering : including machine learning applications / Gebrail Bekdaş, Sinan Melih Nigdeli, editors.
2023
TA636
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Details
Title
Hybrid metaheuristics in structural engineering : including machine learning applications / Gebrail Bekdaş, Sinan Melih Nigdeli, editors.
ISBN
9783031347283 (electronic bk.)
3031347285 (electronic bk.)
9783031347276
3031347277
3031347285 (electronic bk.)
9783031347276
3031347277
Published
Cham : Springer, [2023]
Copyright
©2023
Language
English
Description
1 online resource (viii, 305 pages) : illustrations (some color).
Other Standard Identifiers
10.1007/978-3-031-34728-3 doi
Call Number
TA636
Dewey Decimal Classification
624.1
Summary
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. .
Access Note
Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed June 21, 2023).
Series
Studies in systems, decision and control ; v. 480. 2198-4190
Available in Other Form
Print version: 9783031347276
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Table of Contents
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.
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.