دورية أكاديمية
Firefly algorithm versus genetic algorithm as powerful variable selection tools and their effect on different multivariate calibration models in spectroscopy: A comparative study.
| العنوان: | Firefly algorithm versus genetic algorithm as powerful variable selection tools and their effect on different multivariate calibration models in spectroscopy: A comparative study. |
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| المؤلفون: | Attia KA; Pharmaceutical Analytical Chemistry Department, Faculty of Pharmacy, Al-Azhar University, 11751 Nasr City, Cairo, Egypt., Nassar MW; Pharmaceutical Analytical Chemistry Department, Faculty of Pharmacy, Al-Azhar University, 11751 Nasr City, Cairo, Egypt., El-Zeiny MB; Analytical Chemistry Department, Faculty of Pharmacy, Modern University for Technology and Information (MTI), 12582 Al Hadaba Al Wosta, Cairo, Egypt., Serag A; Pharmaceutical Analytical Chemistry Department, Faculty of Pharmacy, Al-Azhar University, 11751 Nasr City, Cairo, Egypt. Electronic address: Ahmedserag777@hotmail.com. |
| المصدر: | Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy [Spectrochim Acta A Mol Biomol Spectrosc] 2017 Jan 05; Vol. 170, pp. 117-23. Date of Electronic Publication: 2016 Jul 10. |
| نوع المنشور: | Journal Article |
| اللغة: | English |
| بيانات الدورية: | Publisher: Elsevier Country of Publication: England NLM ID: 9602533 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1873-3557 (Electronic) Linking ISSN: 13861425 NLM ISO Abbreviation: Spectrochim Acta A Mol Biomol Spectrosc Subsets: PubMed not MEDLINE |
| أسماء مطبوعة: | Publication: Original Publication: [Kidlington, Oxford, U.K. ; Tarrytown, NY] : Pergamon, c1994- |
| مستخلص: | For the first time, a new variable selection method based on swarm intelligence namely firefly algorithm is coupled with three different multivariate calibration models namely, concentration residual augmented classical least squares, artificial neural network and support vector regression in UV spectral data. A comparative study between the firefly algorithm and the well-known genetic algorithm was developed. The discussion revealed the superiority of using this new powerful algorithm over the well-known genetic algorithm. Moreover, different statistical tests were performed and no significant differences were found between all the models regarding their predictabilities. This ensures that simpler and faster models were obtained without any deterioration of the quality of the calibration. (Copyright © 2016 Elsevier B.V. All rights reserved.) |
| فهرسة مساهمة: | Keywords: Artificial neural network; Concentration residual augmented classical least squares; Firefly algorithm; Genetic algorithm; Support vector regression |
| تواريخ الأحداث: | Date Created: 20160717 Date Completed: 20180111 Latest Revision: 20180111 |
| رمز التحديث: | 20221213 |
| DOI: | 10.1016/j.saa.2016.07.016 |
| PMID: | 27423110 |
| قاعدة البيانات: | MEDLINE |
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