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JACIII Vol.28 No.3 pp. 484-493
doi: 10.20965/jaciii.2024.p0484
(2024)

Research Paper:

Leakage Source Location of Hazardous Chemicals Based on the Improved Gray Wolf Optimization Algorithm

Zeng-Qiang Chen ORCID Icon, Yi-Meng Wang, Cong-Cong Qi, and Shao-Kun Zheng

Information Engineering College, Beijing Institute of Petrochemical Technology
No.19 Qingyuan North Road, Huangcun Town, Daxing District, Beijing 102600, China

Corresponding author

Received:
May 30, 2023
Accepted:
November 1, 2023
Published:
May 20, 2024
Keywords:
source inversion, Gaussian diffusion model, leakage source location, gray wolf optimization algorithm
Abstract

To accurately determine the leakage source location and strength during gas leakage accidents, this study compares the concentration obtained from the diffusion model with that measured by the sensor and proposes an improved gray wolf optimization algorithm for leakage source location. This algorithm introduces two improvement strategies. First, a nonlinear convergence factor is introduced to balance the global and local searches of the algorithm. Second, a reverse learning operation is performed on the three individuals with the worst fitness in the contemporary population. The results showed that the location results based on the improved gray wolf optimization algorithm exhibited high accuracy and stability, could quickly and accurately locate the leakage source, and provided data support for emergency disposal of accidents.

IGWO-based leakage source location

IGWO-based leakage source location

Cite this article as:
Z. Chen, Y. Wang, C. Qi, and S. Zheng, “Leakage Source Location of Hazardous Chemicals Based on the Improved Gray Wolf Optimization Algorithm,” J. Adv. Comput. Intell. Intell. Inform., Vol.28 No.3, pp. 484-493, 2024.
Data files:
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Last updated on Jul. 12, 2024