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Subset Sensor Selection Optimization: A Genetic Algorithm Approach with Innovative Set Encoding Methods

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posted on 2023-05-22, 19:31 authored by Aurelien MerayAurelien Meray, Roger Boza, Masudur R. Siddiquee, Cesar Reyes, M. Hadi AminiM. Hadi Amini, Nagarajan Prabakar

The study presents a new approach for solving the sensor subset selection problem using set encoding and genetic algorithms, aiming to minimize the number of sensors while maintaining accurate spatial estimation. The proposed method, tested on groundwater data from the Savannah River Site, introduces novel crossover and mutation methods, outperforming a previous greedy method with an R2 higher than 0.98 for reduced sensor counts.


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Florida International University

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  • United States of America