Journal Article10.1016/J.ANUCENE.2019.107031
Nuclear accident source term estimation using Kernel Principal Component Analysis, Particle Swarm Optimization, and Backpropagation Neural Networks
Yongsheng Ling,Yongsheng Ling,Qi Yue,Chai Chaojun,Qing Shan,Daqian Hei,Wenbao Jia,Wenbao Jia +7 more
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TL;DR: The proposed source term estimation method, based on the Backpropagation Neural Network, can estimate the release rate of I-131 after half an hour of release, which is helpful to the emergency response, or provide an initial value or priori information for other methods.
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About: This article is published in Annals of Nuclear Energy. The article was published on 01 Feb 2020. The article focuses on the topics: Artificial neural network & Kernel principal component analysis.
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Citations
Artificial neural network modeling in environmental radioactivity studies - A review.
TL;DR: An overview of ANN-based modeling in environmental radioactivity studies, including identifying and quantifying radionuclides, predicting their migration in the environment, mapping their distribution, optimizing measurement methodologies, monitoring processes in nuclear plants, and real-time data analysis is presented in this paper .
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Multi-nuclide source term estimation method for severe nuclear accidents from sequential gamma dose rate based on a recurrent neural network
TL;DR: In this paper, a recurrent neural network-based model was proposed to estimate the emission rates of multi-nuclides using off-site sequential gamma dose rate monitoring data, which does not require a priori information and the complicated and time-consuming process of conducting atmospheric dispersion simulations following a nuclear accident.
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Key emergency response technologies for abrupt air pollution accidents in China.
Jun Duan,Shushuai Mao,Pinhua Xie,Jianlei Lang,Ang Li,Jingjing Tong,Min Qin,Jian Xu,Zeya Shen +8 more
TL;DR: A comprehensive emergency response platform integrating database support, source estimation, monitoring schemes, fast monitoring of pollutants, pollution predictions and risk assessment was developed based on the technical idea of "source identification - model simulation - environmental monitoring" dynamic interactive feedback as discussed by the authors .
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Improving source inversion performance of airborne pollutant emissions by modifying atmospheric dispersion scheme through sensitivity analysis combined with optimization model.
TL;DR: In this paper, a novel approach for parameter sensitivity analysis combined with an optimization method was proposed to improve the source inversion performance by optimizing empirical scheme, which can help to obtain more accurate source information and to provide reliable reference for air pollution managements or emergency response to accidents.
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How Social Impressions Affect Public Acceptance of Nuclear Energy: A Case Study in China
TL;DR: Zhang et al. as mentioned in this paper examined the impact of social impression (including impression management and stigmatization), knowledge, social trust, perceived risk, and perceived benefit on the public acceptance of nuclear energy.
References
Kernel Principal Component Analysis
Bernhard Schölkopf,Alexander J. Smola,Klaus-Robert Müller +2 more
- 08 Oct 1997
TL;DR: A new method for performing a nonlinear form of Principal Component Analysis by the use of integral operator kernel functions is proposed and experimental results on polynomial feature extraction for pattern recognition are presented.
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Preliminary Estimation of Release Amounts of ^ I and ^ Cs Accidentally Discharged from the Fukushima Daiichi Nuclear Power Plant into the Atmosphere
Masamichi Chino,Hiromasa Nakayama,Haruyasu Nagai,Hiroaki Terada,Genki Katata,Hiromi Yamazawa +5 more
TL;DR: In this article, the preliminary estimation of release amounts of 131I and 137Cs from the Fukushima Daiichi nuclear power plant into the atmosphere has been presented, with the aim to estimate the amount of radiation released by the plant.
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A hybrid particle swarm optimization-back-propagation algorithm for feedforward neural network training
TL;DR: In this article, a hybrid algorithm combining particle swarm optimization (PSO) algorithm with back-propagation (BP) algorithm, also referred to as PSO-BP algorithm, is proposed to train the weights of feedforward neural network (FNN), the hybrid algorithm can make use of not only strong global searching ability of the PSOA, but also strong local searching capability of the BP algorithm.
698
Face recognition using kernel principal component analysis
TL;DR: Through adopting a polynomial kernel, the principal components can be computed within the space spanned by high-order correlations of input pixels making up a facial image, thereby producing a good performance.
2011 Fukushima Dai-ichi nuclear power plant accident: summary of regional radioactive deposition monitoring results
TL;DR: The results revealed that Fukushima-derived radioactive cloud dominantly affected in the central and eastern part of Honshu-Island, although it affected all of Japanese land area and also western North Pacific.
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