Atmospheric dispersion prediction and source estimation of hazardous gas using artificial neural network, particle swarm optimization and expectation maximization-Reference-Cited by-同舟云学术

Atmospheric dispersion prediction and source estimation of hazardous gas using artificial neural network, particle swarm optimization and expectation maximization

Published:2018-04 Issue: Volume:178 Page:158-163
ISSN:1352-2310
Container-title:Atmospheric Environment
language:en
Short-container-title:Atmospheric Environment

Author:

Qiu Sihang,Chen Bin^ORCID,Wang Rongxiao,Zhu Zhengqiu,Wang Yuan,Qiu Xiaogang

Funder

National Key Research & Development (R&D) Plan

National Natural Science Foundation of China

Guangdong Key Laboratory for Big Data Analysis and Simulation of Public Opinion

China Association for Science and Technology

Publisher

Elsevier BV

Subject

Atmospheric Science,General Environmental Science

Reference34 articles.

1. Improving pollutant source characterization by better estimating wind direction with a genetic algorithm;Allen;Atmos. Environ.,2007

2. Bayesian-based methods for the estimation of the unknown Model's parameters in the case of the localization of the atmospheric contamination source;Borysiewicz;Found. Comput. Decis. Sci.,2012

3. Source term estimation using air concentration measurements and a Lagrangian dispersion model – experiments with pseudo and real cesium-137 observations from the Fukushima nuclear accident;Chai;Atmos. Environ.,2015

4. Air quality model performance evaluation;Chang;Meteorol. Atmos. Phys.,2004

5. Comparison of RIMPUFF, HYSPLIT, ADMS atmospheric dispersion model outputs, using emergency response procedures, with 85Kr measurements made in the vicinity of nuclear reprocessing plant;Connan;J. Environ. Radioact.,2013

Cited by 61 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Natural gas leakage: Forward and inverse method of leakage field based on multipath concentration monitoring;Measurement;2025-01

2. Source term inversion of nuclear accidents based on ISAO-SAELM model;Nuclear Engineering and Technology;2024-09

3. Emission Rate Estimation of Industrial Air Pollutant Emissions Based on Mobile Observation;Atmosphere;2024-08-13

4. Deep learning-based dispersion prediction model for hazardous chemical leaks using transfer learning;Process Safety and Environmental Protection;2024-08

5. Fast dynamic prediction of consequences of heavy gas leakage accidents based on machine learning;Frontiers in Environmental Science;2024-07-23