Application of Genetic Programming for Electrical Engineering Predictive Modeling: A Review

Created by W.Langdon from gp-bibliography.bib Revision:1.8129

@InCollection{Hosseini:2015:hbgpa,

• author = "Seyyed Soheil Sadat Hosseini and Alireza Nemati",
• title = "Application of Genetic Programming for Electrical Engineering Predictive Modeling: A Review",
• booktitle = "Handbook of Genetic Programming Applications",
• publisher = "Springer",
• year = "2015",
• editor = "Amir H. Gandomi and Amir H. Alavi and Conor Ryan",
• chapter = "6",
• pages = "141--154",
• keywords = "genetic algorithms, genetic programming",
• isbn13 = "978-3-319-20882-4",
• DOI = "doi:10.1007/978-3-319-20883-1_6",
• abstract = "The purpose of having computers automatically resolve problems is essential for machine learning, artificial intelligence and a wide area covered by what Turing called machine intelligence. Genetic programming (GP) is an adaptable and strong evolutionary algorithm with some features that can be very priceless and adequate to get computers automatically to address problems starting from a high-level statement of what to do. Using the concept from natural evolution, GP begins from an ooze of random computer programs and improve them progressively through processes of mutation and sexual recombination until solutions appear. All this without the user needing to know or determine the form or structure of solutions in advance. GP has produced a plethora of human-competitive results and applications, involving novel scientific discoveries and patent-able inventions. The goal of this paper is to give an introduction to the quickly developing field of GP. We begin with a gentle introduction to the basic representation, initialization and operators used in GP, completed by a step by step description of their use and application. Then, we progress to explain the diversity of alternative representations for programs and more advanced specializations of GP. Despite the fact that this paper has been written with beginners and practitioners in mind, for completeness we also provide an outline of the theoretical aspect available to date for GP.",
• notes = "Author Affiliations: Department of Electrical Engineering and Computer Science, University of Toledo, Toledo, OH, 43606, USA",

}

Genetic Programming entries for S S Sadat Hosseini Alireza Nemati

Citations