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Differentiation of NaCl, NaOH, and β-Phenylethylamine Using Ultraviolet Spectroscopy and Improved Adaptive Artificial Bee Colony Combined with BP-ANN Algorithm
[Image: see text] The aim of this study is to enhance the classification performance of the back-propagation-artificial neural network (BP-ANN) algorithm for NaCl, NaOH, β-phenylethylamine (PEA), and their mixture, as well as to avoid the defects of the artificial bee colony (ABC) algorithm such as...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10077557/ https://www.ncbi.nlm.nih.gov/pubmed/37033840 http://dx.doi.org/10.1021/acsomega.3c00271 |
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author | Tong, Angxin Tang, Xiaojun Liu, Haibin Gao, Honghu Kou, Xiaofei Zhang, Qiang |
author_facet | Tong, Angxin Tang, Xiaojun Liu, Haibin Gao, Honghu Kou, Xiaofei Zhang, Qiang |
author_sort | Tong, Angxin |
collection | PubMed |
description | [Image: see text] The aim of this study is to enhance the classification performance of the back-propagation-artificial neural network (BP-ANN) algorithm for NaCl, NaOH, β-phenylethylamine (PEA), and their mixture, as well as to avoid the defects of the artificial bee colony (ABC) algorithm such as prematurity and local optimization. In this paper, a method that combined an improved adaptive artificial bee colony (IAABC) algorithm and BP-ANN algorithm was proposed. This method improved the ABC algorithm by adding an adaptive local search factor and mutation factor; meanwhile, it can enhance the abilities of the global optimization and local search of the ABC algorithm and avoid prematurity. The extracted score vectors of the principal component of the ultraviolet (UV) spectrum were used as the input variable of the BP-ANN algorithm. The IAABC algorithm was used to optimize the weight and threshold of the BP-ANN algorithm, and the iterative algorithm was repeated until the output accuracy was reached. The output variable was the classification results of NaCl, NaOH, PEA, and the mixture. Meanwhile, the proposed IAABC-BP-ANN algorithm was compared with discriminant analysis (DA), sigmaid-support vector machine (SVM), radial basis function-SVM (RBF-SVM), BP-ANN, and ABC-BP-ANN. Then, the above algorithms were used to classify NaCl, NaOH, PEA, and the mixture, respectively. In the experiment, four indicators, accuracy, recall, precision, and F-score, were used as the evaluation criteria. In addition, the regression equation parameters of the mixture for the testing set were obtained by BP-ANN, ABC-BP-ANN, and IAABC-BP-ANN models. All of the results showed that IAABC-BP-ANN exhibits better performance than other algorithms. Therefore, IAABC-BP-ANN combined with UV spectroscopy is a potential identification tool for the detection of NaCl, NaOH, PEA, and the mixture. |
format | Online Article Text |
id | pubmed-10077557 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-100775572023-04-07 Differentiation of NaCl, NaOH, and β-Phenylethylamine Using Ultraviolet Spectroscopy and Improved Adaptive Artificial Bee Colony Combined with BP-ANN Algorithm Tong, Angxin Tang, Xiaojun Liu, Haibin Gao, Honghu Kou, Xiaofei Zhang, Qiang ACS Omega [Image: see text] The aim of this study is to enhance the classification performance of the back-propagation-artificial neural network (BP-ANN) algorithm for NaCl, NaOH, β-phenylethylamine (PEA), and their mixture, as well as to avoid the defects of the artificial bee colony (ABC) algorithm such as prematurity and local optimization. In this paper, a method that combined an improved adaptive artificial bee colony (IAABC) algorithm and BP-ANN algorithm was proposed. This method improved the ABC algorithm by adding an adaptive local search factor and mutation factor; meanwhile, it can enhance the abilities of the global optimization and local search of the ABC algorithm and avoid prematurity. The extracted score vectors of the principal component of the ultraviolet (UV) spectrum were used as the input variable of the BP-ANN algorithm. The IAABC algorithm was used to optimize the weight and threshold of the BP-ANN algorithm, and the iterative algorithm was repeated until the output accuracy was reached. The output variable was the classification results of NaCl, NaOH, PEA, and the mixture. Meanwhile, the proposed IAABC-BP-ANN algorithm was compared with discriminant analysis (DA), sigmaid-support vector machine (SVM), radial basis function-SVM (RBF-SVM), BP-ANN, and ABC-BP-ANN. Then, the above algorithms were used to classify NaCl, NaOH, PEA, and the mixture, respectively. In the experiment, four indicators, accuracy, recall, precision, and F-score, were used as the evaluation criteria. In addition, the regression equation parameters of the mixture for the testing set were obtained by BP-ANN, ABC-BP-ANN, and IAABC-BP-ANN models. All of the results showed that IAABC-BP-ANN exhibits better performance than other algorithms. Therefore, IAABC-BP-ANN combined with UV spectroscopy is a potential identification tool for the detection of NaCl, NaOH, PEA, and the mixture. American Chemical Society 2023-03-20 /pmc/articles/PMC10077557/ /pubmed/37033840 http://dx.doi.org/10.1021/acsomega.3c00271 Text en © 2023 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by/4.0/Permits the broadest form of re-use including for commercial purposes, provided that author attribution and integrity are maintained (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Tong, Angxin Tang, Xiaojun Liu, Haibin Gao, Honghu Kou, Xiaofei Zhang, Qiang Differentiation of NaCl, NaOH, and β-Phenylethylamine Using Ultraviolet Spectroscopy and Improved Adaptive Artificial Bee Colony Combined with BP-ANN Algorithm |
title | Differentiation
of NaCl, NaOH, and β-Phenylethylamine
Using Ultraviolet Spectroscopy and Improved Adaptive Artificial Bee
Colony Combined with BP-ANN Algorithm |
title_full | Differentiation
of NaCl, NaOH, and β-Phenylethylamine
Using Ultraviolet Spectroscopy and Improved Adaptive Artificial Bee
Colony Combined with BP-ANN Algorithm |
title_fullStr | Differentiation
of NaCl, NaOH, and β-Phenylethylamine
Using Ultraviolet Spectroscopy and Improved Adaptive Artificial Bee
Colony Combined with BP-ANN Algorithm |
title_full_unstemmed | Differentiation
of NaCl, NaOH, and β-Phenylethylamine
Using Ultraviolet Spectroscopy and Improved Adaptive Artificial Bee
Colony Combined with BP-ANN Algorithm |
title_short | Differentiation
of NaCl, NaOH, and β-Phenylethylamine
Using Ultraviolet Spectroscopy and Improved Adaptive Artificial Bee
Colony Combined with BP-ANN Algorithm |
title_sort | differentiation
of nacl, naoh, and β-phenylethylamine
using ultraviolet spectroscopy and improved adaptive artificial bee
colony combined with bp-ann algorithm |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10077557/ https://www.ncbi.nlm.nih.gov/pubmed/37033840 http://dx.doi.org/10.1021/acsomega.3c00271 |
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