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Evolutionary Computation Techniques for Predicting Atmospheric Corrosion
Author(s) -
Amine Marref,
Saleh Basalamah,
Rami Al-Ghamdi
Publication year - 2013
Publication title -
international journal of corrosion
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.312
H-Index - 18
eISSN - 1687-9333
pISSN - 1687-9325
DOI - 10.1155/2013/805167
Subject(s) - corrosion , genetic algorithm , genetic programming , evolutionary computation , computer science , computation , materials science , biochemical engineering , biological system , metallurgy , engineering , biology , artificial intelligence , algorithm , machine learning
Corrosion occurs in many engineering structures such as bridges, pipelines, and refineries and leads to the destruction of materials in a gradual manner and thus shortening their lifespan. It is therefore crucial to assess the structural integrity of engineering structures which are approaching or exceeding their designed lifespan in order to ensure their correct functioning, for example, carrying ability and safety. An understanding of corrosion and an ability to predict corrosion rate of a material in a particular environment plays a vital role in evaluating the residual life of the material. In this paper we investigate the use of genetic programming and genetic algorithms in the derivation of corrosion-rate expressions for steel and zinc. Genetic programming is used to automatically evolve corrosion-rate expressions while a genetic algorithm is used to evolve the parameters of an already engineered corrosion-rate expression. We show that both evolutionary techniques yield corrosion-rate expressions that have good accuracy

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