A Hybrid Neural Network-Genetic Programming Intelligent Control Approach

Created by W.Langdon from gp-bibliography.bib Revision:1.8010

@InProceedings{Marchetti:2020:BIOMA,

• author = "Francesco Marchetti and Edmondo Minisci",
• title = "A Hybrid Neural Network-Genetic Programming Intelligent Control Approach",
• booktitle = "Bioinspired Optimization Methods and Their Applications. BIOMA 2020",
• year = "2020",
• editor = "Bogdan Filipic and Edmondo Minisci and Massimiliano Vasile",
• volume = "12438",
• series = "Lecture Notes in Computer Science",
• pages = "240--254",
• address = "Brussels, Belgium",
• month = "19-20 " # nov,
• publisher = "Springer",
• keywords = "genetic algorithms, genetic programming, Intelligent Control, Neural Networks, ANN, optimal control, space transportation system, Electronic computers. Computer science, Theoretical Computer Science, Aerospace Engineering",
• isbn13 = "978-3-030-63709-5",
• URL = "https://strathprints.strath.ac.uk/74956/",
• DOI = "doi:10.1007/978-3-030-63710-1_19",
• abstract = "The proposed work aims to introduce a novel approach to Intelligent Control (IC), based on the combined use of Genetic Programming (GP) and feedforward Neural Network (NN). Both techniques have been successfully used in the literature for regression and control applications, but, while a NN creates a black box model, GP allows for a greater interpretability of the created model, which is a key feature in control applications. The main idea behind the hybrid approach proposed in this paper is to combine the speed and flexibility of a NN with the interpretability of GP. Moreover, to improve the robustness of the GP control law against unforeseen environmental changes, a new selection and crossover mechanisms, called Inclusive Tournament and Inclusive Crossover, are also introduced. The proposed IC approach is tested on the guidance control of a space transportation system and results, showing the potentialities for real applications, are shown and discussed.",
• notes = "also known as \cite{strathprints74956}",

}

Genetic Programming entries for Francesco Marchetti Edmondo Minisci

Citations