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| Content Provider | World Health Organization (WHO)-Global Index Medicus |
|---|---|
| Author | Goodarzi, Mohammad Dos Santos Coelho, Leandro |
| Description | Author Affiliation: Goodarzi M ( Department of Biosystems, Faculty of Bioscience Engineering, Katholieke Universiteit Leuven - KU Leuven, Kasteelpark Arenberg 30, Heverlee B-3001, Belgium. Electronic address: mohammad.godarzi@gmail.com.); dos Santos Coelho L ( Department of Electrical Engineering, Federal University of Parana (UFPR), Rua Cel. Francisco Heraclito dos Santos, 100, Curitiba, PR 81531-980, Brazil) |
| 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. This paper represents a novel feature selection approach to the selection of spectroscopic data, leading to more robust calibration models. The performance of the firefly algorithm, a swarm intelligence paradigm, was evaluated and compared with genetic algorithm and particle swarm optimization. All three techniques were coupled with partial least squares (PLS) and applied to three spectroscopic data sets. They demonstrate improved prediction results in comparison to when only a PLS model was built using all wavelengths. Results show that firefly algorithm as a novel swarm paradigm leads to a lower number of selected wavelengths while the prediction performance of built PLS stays the same. |
| File Format | HTM / HTML |
| ISSN | 00032670 |
| Volume Number | 852 |
| e-ISSN | 18734324 |
| Journal | Analytica Chimica Acta |
| Language | English |
| Publisher | Elsevier |
| Publisher Date | 2014-12-10 |
| Publisher Place | Netherlands |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Discipline Analytical Discipline Chemistry Algorithms Artificial Intelligence Spectroscopy, Fourier Transform Infrared Methods Animals Calibration Fireflies Physiology Least-squares Analysis Journal Article |
| Content Type | Text |
| Resource Type | Article |
| Subject | Spectroscopy Environmental Chemistry Analytical Chemistry Biochemistry |
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