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个人信息Personal Information
副教授 硕士生导师
招生学科专业：
核科学与技术 -- 【招收硕士研究生】 -- 材料科学与技术学院
能源动力 -- 【招收硕士研究生】 -- 材料科学与技术学院
性别：男
毕业院校：清华大学
学历：清华大学
学位：工学博士学位
所在单位：材料科学与技术学院
办公地点：南京航空航天大学江宁校区西区材料楼325办公室
联系方式：lingyongsheng@nuaa.edu.cn
电子邮箱：
Nuclear accident source term estimation using Kernel Principal Component Analysis, Particle Swarm Optimization, and Backpropagation Neural Networks
点击次数：
所属单位：材料科学与技术学院
发表刊物：Ann Nucl Energy
摘要：Rapid estimation of the release rate of source items after a nuclear accident is very important for nuclear emergency and decision making. A source term estimation method, based on the Backpropagation Neural Network (BPNN), was developed. Kernel Principal Component Analysis (KPCA) is used to reduce the dimension of the input parameters, which can accelerate the training of the neural network. Particle Swarm Optimization (PSO) is used to optimize weights and thresholds of BPNN, so that the neural network can better find the global optimal value, avoid falling into the local minimum. The large amount of data required for neural network training is generated using InterRAS software, the model constructed demonstrates the feasibility of this method. The proposed method 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. © 2019 Elsevier Ltd
ISSN号：0306-4549
是否译文：否
发表时间：2020-02-01
合写作者：岳勤,Chai, Chaojun,Shan, Qing,F70205423,贾文宝
通讯作者：凌永生