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Wenqian CAI,Wei MENG,Lusan LIU,Kuixuan LIN
《环境科学与工程前沿(英文)》 2014年 第8卷 第5期 页码 737-746 doi: 10.1007/s11783-013-0617-x
关键词: AZTI’s Marine Biotic Index Shannon-Wiener Index W-statistic ecological status coastal system Bohai Bay (China)
ZHANG Jian, Lu Yifeng, JING Yuming, ZHANG Bo, ZHANG Chenglu, MENG Fei, ZHANG Huayong
《环境科学与工程前沿(英文)》 2008年 第2卷 第3期 页码 306-310 doi: 10.1007/s11783-008-0057-1
关键词: community South-to-North Shannon-Wiener Evenness addition
Sequential degradation-based burn-in test with multiple periodic inspections
《工程管理前沿(英文)》 2021年 第8卷 第4期 页码 519-530 doi: 10.1007/s42524-021-0166-0
关键词: burn-in degradation multiple inspections Wiener process partially observed Markov decision process
Bayes estimation of residual life by fusing multisource information
Qian ZHAO, Xiang JIA, Zhi-jun CHENG, Bo GUO
《工程管理前沿(英文)》 2018年 第5卷 第4期 页码 524-532 doi: 10.15302/J-FEM-2018034
Residual life estimation is essential for reliability engineering. Traditional methods may experience difficulties in estimating the residual life of products with high reliability, long life, and small sample. The Bayes model provides a feasible solution and can be a useful tool for fusing multisource information. In this study, a Bayes model is proposed to estimate the residual life of products by fusing expert knowledge, degradation data, and lifetime data. The linear Wiener process is used to model degradation data, whereas lifetime data are described via the inverse Gaussian distribution. Therefore, the joint maximum likelihood (ML) function can be obtained by combining lifetime and degradation data. Expert knowledge is used according to the maximum entropy method to determine the prior distributions of parameters, thereby making this work different from existing studies that use non-informative prior. The discussion and analysis of different types of expert knowledge also distinguish our research from others. Expert knowledge can be classified into three categories according to practical engineering. Methods for determining prior distribution by using the aforementioned three types of data are presented. The Markov chain Monte Carlo is applied to obtain samples of the parameters and to estimate the residual life of products due to the complexity of the joint ML function and the posterior distribution of parameters. Finally, a numerical example is presented. The effectiveness and practicability of the proposed method are validated by comparing it with residual life estimation that uses non-informative prior. Then, its accuracy and correctness are proven via simulation experiments.
关键词: residual life estimation Bayes model linear Wiener process
罗茜倩,张朝阳
《信息与电子工程前沿(英文)》 2021年 第22卷 第2期 页码 141-286 doi: 10.1631/FITEE.1900320
标题 作者 时间 类型 操作
Evaluation of the ecological status with benthic indices in the coastal system: the case of Bohai Bay (China)
Wenqian CAI,Wei MENG,Lusan LIU,Kuixuan LIN
期刊论文
Ecological assessment of lakeshore wetland rehabilitation on eastern route of South-to-North Water Transfer Project
ZHANG Jian, Lu Yifeng, JING Yuming, ZHANG Bo, ZHANG Chenglu, MENG Fei, ZHANG Huayong
期刊论文
Bayes estimation of residual life by fusing multisource information
Qian ZHAO, Xiang JIA, Zhi-jun CHENG, Bo GUO
期刊论文