Chapter 19 - Multigene genetic programming and its various applications

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@InCollection{NIAZKAR:2023:HH,

• author = "Majid Niazkar",
• title = "Chapter 19 - Multigene genetic programming and its various applications",
• editor = "Saeid Eslamian and Faezeh Eslamian",
• booktitle = "Handbook of Hydroinformatics",
• publisher = "Elsevier",
• pages = "321--332",
• year = "2023",
• isbn13 = "978-0-12-821285-1",
• DOI = "doi:10.1016/B978-0-12-821285-1.00019-1",
• URL = "https://www.sciencedirect.com/science/article/pii/B9780128212851000191",
• keywords = "genetic algorithms, genetic programming, Multigene genetic programming, Artificial intelligence models, Crossover, Mutation, Prediction tool, Soft-computing, Machine learning",
• abstract = "This chapter reviews a modified version of genetic programming, so-called multigene genetic programming (MGGP). It is basically one of artificial intelligence models and capable of searching for a suitable relationship between any input and output sets of data, regardless of the physical background of the data. Since it has a flexible structure and powerful search engine, it has inevitable potential to be used for solving various problems in different field of research including water resources management. In this regard, this chapter aims to introduce this technique and its merits. First, it begins with genetic programming and its different versions. Afterward, multigene genetic programming and its main controlling parameters are introduced. A brief literature review on application of multigene genetic programming is presented, while some applications are suggested for using multigene genetic programming for future studies. Furthermore, the problem of developing stage-discharge rating curves is revisited, and a new MGGP-based model is proposed. Finally, the results indicate that MGGP-based models outperformed other methods considered in the comparative analysis",

}

Genetic Programming entries for Majid Niazkar

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