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Gene Expression Programming

Gene Expression Programming

Baddrud Zaman Laskar, Swanirbhar Majumder
Copyright: © 2021 |Pages: 20
ISBN13: 9781799880486|ISBN10: 1799880486|EISBN13: 9781799880998
DOI: 10.4018/978-1-7998-8048-6.ch022
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MLA

Laskar, Baddrud Zaman, and Swanirbhar Majumder. "Gene Expression Programming." Research Anthology on Multi-Industry Uses of Genetic Programming and Algorithms, edited by Information Resources Management Association, IGI Global, 2021, pp. 427-446. https://doi.org/10.4018/978-1-7998-8048-6.ch022

APA

Laskar, B. Z. & Majumder, S. (2021). Gene Expression Programming. In I. Management Association (Ed.), Research Anthology on Multi-Industry Uses of Genetic Programming and Algorithms (pp. 427-446). IGI Global. https://doi.org/10.4018/978-1-7998-8048-6.ch022

Chicago

Laskar, Baddrud Zaman, and Swanirbhar Majumder. "Gene Expression Programming." In Research Anthology on Multi-Industry Uses of Genetic Programming and Algorithms, edited by Information Resources Management Association, 427-446. Hershey, PA: IGI Global, 2021. https://doi.org/10.4018/978-1-7998-8048-6.ch022

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Abstract

Gene expression programming (GEP) introduced by Candida Ferreira is a descendant of genetic algorithm (GA) and genetic programming (GP). It takes the advantage of both the optimization and search technique based on genetics and natural selection as GA and its programmatic Darwinian counterpart GP. It is gaining popularity because; it has to some extent eradicated the ‘cons' of both while keeping in the ‘pros'. It is still a new technique not much explored since its introduction in 2001. In this chapter both GA and GP is first discussed followed by the elaborate discussion of GEP. This is followed up by the discussion on research work done is different fields using GEP as a tool followed up by GEP architectures. Finally, here GEP has been used for detection of age from facial features as a soft computing based optimization problem using genetic operators.

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