The hazardous or toxic chemical releases have a detrimental impact on public safety. Estimating source parameters is of particular importance in aiding emergency response and post-assessment. Source term estimation from sensor measurements with a given Gaussian puff dispersion model is a typical inverse problem, which can be transformed into an optimization problem. In this paper, we employed the particle swarm optimization, the Nelder–Mead method, and their hybrid method to solve the optimization problem. Furthermore, we proposed a three-dimensional neighborhood topology which considerably improves performance of the particle swarm optimization. We implemented all these algorithms in JAVA on an embedded system to make a preliminary estimation of the accidental puff release. Numerical experiments with synthetic datasets show that the particle swarm optimization maintains a balance between computation time, accuracy, robustness, and implementation complexity. In contrast, the hybrid algorithm has an advantage in computation time at the expense of more sophisticated implementation.
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This work was supported by the National Natural Science Foundation of China under grants of the general technical foundation research joint fund (Project No. U1636208). And this project was also supported by the Ministry of Science and Technology of China under grants of the national key technology R&D program (Project No. 2015BAK39B02).
Compliance with ethical standards
Conflict of interest
We declare that we have no financial and personal relationships with other people or organizations that can inappropriately influence our work, there is no professional or other personal interest of any nature or kind in any product, service and/or company that could be construed as influencing the position presented in, or the review of, the manuscript entitled.
Human and animals rights
This article does not contain any studies with human participants or animals performed by any of the authors.
Informed consent was obtained from all individual participants included in the study.
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