Stress Analysis of 2D-FG Rectangular Plates with Multi-Gene Genetic Programming

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@Article{demirbas:2022:AS,

• author = "Munise Didem Demirbas and Didem Cakir and Celal Ozturk and Sibel Arslan",
• title = "Stress Analysis of {2D-FG} Rectangular Plates with Multi-Gene Genetic Programming",
• journal = "Applied Sciences",
• year = "2022",
• volume = "12",
• number = "16",
• pages = "Article No. 8198",
• keywords = "genetic algorithms, genetic programming",
• ISSN = "2076-3417",
• URL = "https://www.mdpi.com/2076-3417/12/16/8198",
• DOI = "doi:10.3390/app12168198",
• abstract = "Functionally Graded Materials (FGMs) are designed for use in high-temperature applications. Since the mass production of FGM has not yet been made, the determination of its thermo-mechanical limits depends on the compositional gradient exponent value. In this study, an efficient working model is created for the thermal stress problem of the 2D-FG plate using Multi-gene Genetic Programming (MGGP). In our MGGP model in this study, data sets obtained from the numerical analysis results of the thermal stress problem are used, and formulas that give equivalent stress levels as output data, with the input data being the compositional gradient exponent, are obtained. For the current problem, efficient models that reduce CPU processing time are obtained by using the MGGP method.",
• notes = "also known as \cite{app12168198}",

}

Genetic Programming entries for Munise Didem Demirbas Didem Cakir Celal Ozturk Sibel Arslan

Citations