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Inversion of source information in multi-factor optimized Gaussian model by using chaotic mapping-based adaptive firefly algorithm
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Jinyu LUO1, 2, Yongqiang WANG2, Shengzhu ZHANG3, Limin DENG1, 4, Minjun PENG1, 4, Niansheng KUAI**, 1, 4
China Safety Science Journal | 2025, 35(12) : 139 - 146
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China Safety Science Journal | 2025, 35(12): 139-146
• Safety engineering technology •
Inversion of source information in multi-factor optimized Gaussian model by using chaotic mapping-based adaptive firefly algorithm
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Jinyu LUO1, 2, Yongqiang WANG2, Shengzhu ZHANG3, Limin DENG1, 4, Minjun PENG1, 4, Niansheng KUAI**, 1, 4
Affiliations
  • 1Sichuan Institute of Safety Science and Technology, Chengdu Sichuan 610045, China
  • 2School of Environment and Resources, Southwest University of Science and Technology, Mianyang Sichuan 621010, China
  • 3China Academy of Safety and Technology, Beijing 100012, China
  • 4Major Hazard Monitoring and Emergency Response Key Laboratory of Sichuan Province, Chengdu Sichuan 610045, China
Published: 2025-12-28 doi: 10.16265/j.cnki.issn1003-3033.2025.12.0732
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To qucikly obtain the source strength and location information from hazardous gas leakage incidents, a multi-factor optimized Gaussian plume dispersion model was proposed, and the leakage source parameters were inverted by combining it with a CAFA. Key environmental factors such as wind speed distribution, surface resistance, and surface reflection were incorporated into the Gaussian plume model to enhance its fitting capability under complex conditions through multi-factor calibration. Furthermore, a chaotic mapping was introduced to improve the population diversity and global search ability of firefly algorithm(FA), thereby achieving an effective balance between global optimization and local refinement while reducing the risk of falling into local optima. The results indicate that, after optimization based on wind speed distribution, surface resistance, and surface reflection, the error of the Gaussian plume model is reduced by 16%. CAFA effectively can avoid falling into local optima, reducing the source strength inversion error from 63.56% to 0.22%, and the leak source coordinate inversion error from 1.5 m to 0.2 m.

chaos-mapped adaptive firefly algorithm(CAFA)  /  Gaussian plume model  /  hazardous gas leakage  /  source term inversion  /  chemical industrial park
Jinyu LUO, Yongqiang WANG, Shengzhu ZHANG, Limin DENG, Minjun PENG, Niansheng KUAI. Inversion of source information in multi-factor optimized Gaussian model by using chaotic mapping-based adaptive firefly algorithm[J]. China Safety Science Journal, 2025 , 35 (12) : 139 -146 . DOI: 10.16265/j.cnki.issn1003-3033.2025.12.0732
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Year 2025 volume 35 Issue 12
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Article Info
doi: 10.16265/j.cnki.issn1003-3033.2025.12.0732
  • Receive Date：2025-07-20
  • Online Date：2026-07-09
  • Published：2025-12-28
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  • Received：2025-07-20
  • Revised：2025-10-19
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Affiliations
    1Sichuan Institute of Safety Science and Technology, Chengdu Sichuan 610045, China
    2School of Environment and Resources, Southwest University of Science and Technology, Mianyang Sichuan 621010, China
    3China Academy of Safety and Technology, Beijing 100012, China
    4Major Hazard Monitoring and Emergency Response Key Laboratory of Sichuan Province, Chengdu Sichuan 610045, China
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表12种不同金属材料的力学参数
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小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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