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Springer Advances in Structural Engineering Optimization - Springer

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Description

This comprehensive volume explores cutting-edge computation applications for structural optimization, artificial intelligence prediction methods, and evaluation of metaheuristic algorithms across diverse structural applications. As metaheuristic algorithms continue to advance, they address complex and non-optimized problems that challenge traditional mathematical approaches, offering researchers powerful tools for solving next-generation engineering challenges. The book emphasises the critical role of artificial intelligence in predicting optimal results whilst bypassing lengthy iterative optimization processes, and incorporates machine learning techniques to accelerate design solutions. Part of Springer's Studies in Systems, Decision and Control series (volume 326), this resource is essential for professionals and academics seeking to understand current trends in structural optimization and apply emerging computational methods to real-world engineering problems.

Key Features

Covers metaheuristic algorithms as high-interest solutions for advanced and non-optimized structural problems that traditional mathematical methods struggle to address.

Explores artificial intelligence prediction methods to determine optimum structural results without requiring lengthy iterative optimization cycles.

Presents machine learning applications within structural engineering optimization to enhance design efficiency and accuracy.

Includes computation applications demonstrating how optimization techniques are applied to various structural engineering scenarios.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
05 December 2020
Listed Since
12 September 2020

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