Genetic programming based Choquet integral for multi-source fusion

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

@InProceedings{Smith:2017:FUZZ-IEEE,

• author = "Ryan E. Smith and Derek T. Anderson and Alina Zare and John E. Ball and Brandon Smock and Josh R. Fairley and Stacy E. Howington",
• booktitle = "2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)",
• title = "Genetic programming based Choquet integral for multi-source fusion",
• year = "2017",
• abstract = "While the Choquet integral (Chi) is a powerful parametric nonlinear aggregation function, it has limited scope and is not a universal function generator. Herein, we focus on a class of problems that are outside the scope of a single Chi. Namely, we are interested in tasks where different subsets of inputs require different Chls. Herein, a genetic program (GF) is used to extend the Chi, referred to as GpChI hereafter, specifically in terms of compositions of Chls and/or arithmetic combinations of Chls. An algorithm is put forth to learn the different GP Chls via genetic algorithm (GA) optimisation. Synthetic experiments demonstrate GpChI in a controlled fashion, i.e., we know the answer and can compare what is learnt to the truth. Real-world experiments are also provided for the multi-sensor fusion of electromagnetic induction (EMI) and ground penetrating radar (GPR) for explosive hazard detection. Our multi-sensor fusion experiments show that there is utility in changing aggregation strategy per different subsets of inputs (sensors or algorithms) and fusing those results.",
• keywords = "genetic algorithms, genetic programming, Choquet integral, fuzzy integral, multi-sensor fusion",
• DOI = "doi:10.1109/FUZZ-IEEE.2017.8015481",
• month = jul,
• notes = "Also known as \cite{8015481}",

}

Genetic Programming entries for Ryan E Smith Derek T Anderson Alina Zare John E Ball Brandon Smock Josh R Fairley Stacy E Howington

Citations