Firefly as a novel swarm intelligence variable selection method in spectroscopy |
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Authors: | Mohammad Goodarzi Leandro dos Santos Coelho |
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Institution: | 1. Department of Biosystems, Faculty of Bioscience Engineering, Katholieke Universiteit Leuven – KU Leuven, Kasteelpark Arenberg 30, Heverlee B-3001, Belgium;2. Department of Electrical Engineering, Federal University of Parana (UFPR), Rua Cel. Francisco Heraclito dos Santos, 100, Curitiba, PR 81531-980, Brazil;3. Industrial and Systems Engineering Graduate Program (PPGEPS), Pontifical Catholic University of Parana (PUCPR), Rua Imaculada Conceição, 1155, Curitiba, PR 80215-901, Brazil |
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Abstract: | A critical step in multivariate calibration is wavelength selection, which is used to build models with better prediction performance when applied to spectral data. Up to now, many feature selection techniques have been developed. Among all different types of feature selection techniques, those based on swarm intelligence optimization methodologies are more interesting since they are usually simulated based on animal and insect life behavior to, e.g., find the shortest path between a food source and their nests. This decision is made by a crowd, leading to a more robust model with less falling in local minima during the optimization cycle. |
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Keywords: | Firefly algorithm Variable selection Chemometrics Spectroscopy |
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