An artificial intelligence optimization of NOx conversion efficiency under dual catalytic mechanism reaction based on multi-objective gray wolf algorithm
In the era of industry 4.0, artificial intelligence (AI) offers new perspectives for researching the complex sustainable chemical reactions in selective catalytic reduction (SCR). This aims to further improve the utilization and efficiency of SCR. In this study, a fuzzy gray relational analysis coup...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-04-01
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| Series: | Fuel Processing Technology |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S0378382025000062 |
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| author | Zhiqing Zhang Zicheng He Yuguo Wang Feng Jiang Weihuang Zhong Bin Zhang Yanshuai Ye Zibin Yin Dongli Tan |
| author_facet | Zhiqing Zhang Zicheng He Yuguo Wang Feng Jiang Weihuang Zhong Bin Zhang Yanshuai Ye Zibin Yin Dongli Tan |
| author_sort | Zhiqing Zhang |
| collection | DOAJ |
| description | In the era of industry 4.0, artificial intelligence (AI) offers new perspectives for researching the complex sustainable chemical reactions in selective catalytic reduction (SCR). This aims to further improve the utilization and efficiency of SCR. In this study, a fuzzy gray relational analysis coupled with random forest (RF) and back propagation artificial neural network (BP-ANN) model was developed. This model was trained based on the Langmuir-Hinshelwood and Eley-Rideal coupled mechanism for SCR reaction mechanism, and had good fitting effect on the heat transfer rate, catalytic efficiency and ammonia (NH3) slip rate of the catalytic reaction under loading conditions. And this was used as a guiding method to direct the multi-objective gray wolf optimization algorithm to optimize the basic parameters. The optimization results showed that the NH3 slip rate of the SCR was slightly improved and the denitrification efficiency was increased up to 28 % under different loads, which had guiding significance for the lightweighting and thermal control of industrial equipment. |
| format | Article |
| id | doaj-art-0d8f4d2595b044439c5f92f84ef9d8f2 |
| institution | Kabale University |
| issn | 0378-3820 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Fuel Processing Technology |
| spelling | doaj-art-0d8f4d2595b044439c5f92f84ef9d8f22025-02-09T04:59:41ZengElsevierFuel Processing Technology0378-38202025-04-01268108182An artificial intelligence optimization of NOx conversion efficiency under dual catalytic mechanism reaction based on multi-objective gray wolf algorithmZhiqing Zhang0Zicheng He1Yuguo Wang2Feng Jiang3Weihuang Zhong4Bin Zhang5Yanshuai Ye6Zibin Yin7Dongli Tan8School of Mechanical and Automotive Engineering, Guangxi University of Science and Technology, Liuzhou 545006, ChinaSchool of Mechanical and Automotive Engineering, Guangxi University of Science and Technology, Liuzhou 545006, ChinaCollege of Transportation and Navigation, Quanzhou Normal University, Quanzhou 362000, ChinaSchool of Mechanical and Automotive Engineering, Guangxi University of Science and Technology, Liuzhou 545006, China; Corresponding authors.School of Mechanical and Automotive Engineering, Guangxi University of Science and Technology, Liuzhou 545006, China; Corresponding authors.School of Electrical and Information Engineering, Hunan Institute of Engineering, Xiangtan 411104, ChinaSchool of Mechanical and Automotive Engineering, Guangxi University of Science and Technology, Liuzhou 545006, ChinaSchool of Marine Engineering, Jimei University, Xiamen 361021, ChinaSchool of Mechanical and Automotive Engineering, Guangxi University of Science and Technology, Liuzhou 545006, ChinaIn the era of industry 4.0, artificial intelligence (AI) offers new perspectives for researching the complex sustainable chemical reactions in selective catalytic reduction (SCR). This aims to further improve the utilization and efficiency of SCR. In this study, a fuzzy gray relational analysis coupled with random forest (RF) and back propagation artificial neural network (BP-ANN) model was developed. This model was trained based on the Langmuir-Hinshelwood and Eley-Rideal coupled mechanism for SCR reaction mechanism, and had good fitting effect on the heat transfer rate, catalytic efficiency and ammonia (NH3) slip rate of the catalytic reaction under loading conditions. And this was used as a guiding method to direct the multi-objective gray wolf optimization algorithm to optimize the basic parameters. The optimization results showed that the NH3 slip rate of the SCR was slightly improved and the denitrification efficiency was increased up to 28 % under different loads, which had guiding significance for the lightweighting and thermal control of industrial equipment.http://www.sciencedirect.com/science/article/pii/S0378382025000062Selective catalytic reductionMulti-objective optimizationArtificial intelligenceMachine learningDiesel engine |
| spellingShingle | Zhiqing Zhang Zicheng He Yuguo Wang Feng Jiang Weihuang Zhong Bin Zhang Yanshuai Ye Zibin Yin Dongli Tan An artificial intelligence optimization of NOx conversion efficiency under dual catalytic mechanism reaction based on multi-objective gray wolf algorithm Fuel Processing Technology Selective catalytic reduction Multi-objective optimization Artificial intelligence Machine learning Diesel engine |
| title | An artificial intelligence optimization of NOx conversion efficiency under dual catalytic mechanism reaction based on multi-objective gray wolf algorithm |
| title_full | An artificial intelligence optimization of NOx conversion efficiency under dual catalytic mechanism reaction based on multi-objective gray wolf algorithm |
| title_fullStr | An artificial intelligence optimization of NOx conversion efficiency under dual catalytic mechanism reaction based on multi-objective gray wolf algorithm |
| title_full_unstemmed | An artificial intelligence optimization of NOx conversion efficiency under dual catalytic mechanism reaction based on multi-objective gray wolf algorithm |
| title_short | An artificial intelligence optimization of NOx conversion efficiency under dual catalytic mechanism reaction based on multi-objective gray wolf algorithm |
| title_sort | artificial intelligence optimization of nox conversion efficiency under dual catalytic mechanism reaction based on multi objective gray wolf algorithm |
| topic | Selective catalytic reduction Multi-objective optimization Artificial intelligence Machine learning Diesel engine |
| url | http://www.sciencedirect.com/science/article/pii/S0378382025000062 |
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