A review of source term estimation methods for atmospheric dispersion events using static or mobile sensors
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This paper presents a review of techniques used to gain information about atmospheric dispersion events using static or mobile sensors and discusses on the current limitations of the state of the art and recommendations for future research.About:
This article is published in Information Fusion.The article was published on 2017-07-01 and is currently open access. It has received 202 citations till now. The article focuses on the topics: Atmospheric dispersion modeling.read more
Citations
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Particle swarm optimization for source localization in realistic complex urban environments
TL;DR: It is found that PSO works well in idealized and real cases, and can be used to inform first responders or create a tool that can be implemented on UAVs to locate a contaminant source.
Journal ArticleDOI
Determination of radiological background fields designated for inverse modelling during atypical low wind speed meteorological episode
TL;DR: In this article, the formation of complex trajectories of radiological background fields for atypical accidental discharges of radioactivity into the atmosphere during very low wind speed episodes (calms).
Journal ArticleDOI
The effects of air pollution sources / sensor array configurations on the likelihood of obtaining accurate source term estimations
TL;DR: The effect of sensor array/leak configurations on the reliability of the source term estimation is studied using two new measures that can be implemented as a design tool using a combination of computer simulation and field experiments before operational deployment.
Journal ArticleDOI
Machine Learning Emulation of Spatial Deposition from a Multi-Physics Ensemble of Weather and Atmospheric Transport Models
TL;DR: In this paper, a machine-learning-based method was proposed to predict deposition in more than 100,000 grid cells with as few as fifty training examples using a hybrid linear and logistic regression method.
Proceedings ArticleDOI
A Distributed Level Curve Tracking Control Law for Multi-Agent Systems
Said Al-Abri,Fumin Zhang +1 more
TL;DR: This paper presents a distributed control law that does not rely on the communication of the field measurements nor the estimation of the gradient, which scales to large swarms with connected undirected visibility graph.
References
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Posted Content
On Information and Sufficiency
TL;DR: The information deviation between any two finite measures cannot be increased by any statistical operations (Markov morphisms) and is invarient if and only if the morphism is sufficient for these two measures as mentioned in this paper.