Chapter Four - Computational Intelligence Modelling

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Abstract

The development of new materials and faster computing processes opened new frontier for the conception and development of new and audacious designs that will set the trend for the future 21th century structures. Various methods, techniques, and procedures have been, and still are being, used to improve and design these structures like optimisation processes, numerical modelling systems involving non-linear finite element analysis, etc. Concurrently, the last decade of the 20th century has been related to a large improvement and development of the so-called Computational Intelligent Techniques. These techniques are computational systems that try to mimic human behaviour, such as perception, reasoning, learning, evolution, and adaptation. They involve Neural Networks, Genetic Algorithm, Fuzzy Logic, and Hybrid Intelligent Systems, such as Neuro-Fuzzy, Neuro-Genetic, and Fuzzy-Genetic models.

This chapter highlights some of the initial attempts to use Computational Intelligent methods to forecast, design, and optimise the structural behaviour. This work focuses on some of these methods to enable a deeper insight of a wide range of structural engineering applications that could be aided by their proper use. This chapter initially presents a brief description of the adopted Computational Intelligence method, followed by some applications. First two basic artificial neural network models (Multi-Layer Perceptron with Back Propagation algorithm and Bayesian Neural Networks) are introduced. This is followed by the Genetic Algorithms and Genetic Programming. Finally, a brief overview of Neuro-Fuzzy systems was provided, as well as some of its applications to structural engineering. The case studies corroborate the great potential of Computational Intelligence techniques to solve problems that were considered difficult, limited, or even impossible by many researchers in different fields. Some case studies had a performance, in some cases, beyond expected, suggesting that these techniques might be a good solution in many other structural engineering applications.

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