作者机构：
[张力; 李鹏程; 戴立操] Human Factor Institute, University of South China, Hengyang, China;[赵明] CNNP Nuclear Power Operations Management Co., Ltd., Haiyan, China;[胡鸿; 张力] Institute of Human Factor and Safety Management, Hunan Institute of Technology, Hengyang, China
通讯机构：
Human Factor Institute, University of South China, Hengyang, China
期刊：
PSAM 2014 - Probabilistic Safety Assessment and Management,2014年
作者机构：
[Zhang, Li; Zou, Yanhua] Institute of Human Factors Engineering and Safety Management, Hunan Institute of Technology, Hengyang, China;[Zhang, Li; Dai, Licao; Zou, Yanhua; Li, Pengcheng] Human Factor Institute, University of South China, Hengyang, China;[Zhang, Li; Zou, Yanhua] School of Nuclear Science and Technology, University of South China, Hengyang, China
摘要：
The current human reliability analysis method of analyzing system operator's reliability, carried out from the perspective of operators themselves, is relatively static, for it hasn't taken the effect of system evolution on the operators' performance into consideration. In view of operator reliability in digital control system in nuclear power plant, this paper, based on boolean network theory, tries to explore the operators' behavior in the dynamic logic process of system evolution, aiming at finding out the dynamic evolution process of human-system interaction. A new technique, called the semi-tensor product of matrices, can convert the logical systems into standard discrete-time dynamic systems, and then the discrete-time linear equation and reliability analysis model are established. Data collected from simulation experiments carried out in full-size simulator in LingDong Nuclear Power Plant is found to be in consistence with the operator reliability model constructed before.
期刊：
Lecture Notes in Electrical Engineering,2013年209(1):419-426 ISSN：1876-1100
通讯作者：
Yi, Y.X.(yyx19999@126.com)
作者机构：
[Liu, Mengya; Yi, Yong Xi] College of Economics and Management, University of South China, Hengyang 421001, China;[Li, Shoude] Antai College of Economics and Management, Shanghai Jiao Tong University, Shanghai 200052, China
期刊：
Journal of Applied Sciences,2013年13(13):2614-2617 ISSN：1812-5654
通讯作者：
Liu, B.
作者机构：
[Hu, Shuai; Liu, Baoping] College of Economics and Management, University of South China, P.O. Box 421001, Hengyang City, Hunan Province, China;[Rong, Lishan] City Construction College, University of South China, P.O. Box 421001, Hengyang City, Hunan Province, China
摘要：
Customer relationship management (CRM) is an integral part in the manufacturing enterprise information. The content of CRM is based on customer information and business transaction data, and using computer information technology to deeply analysis massive data of data warehouse. The purpose is to identify customers’ different features and analyze customer behaviors, then dig out the information of commercial value to help business planning and decision-making related business activities. The thesis introduces the system of the CRM based on Data Warehouse: to describe and predict the model of enterprise customers’ behavior by data warehouse and data mining theory and technology. The purpose is to optimize the entire CRM process, and effectively realize customer relationship management ultimately. Research and analysis of data warehouse in CRM to achieve other functions such as customer behavior analysis, key customers found and market performance evaluation. It can further analyze amounts of customer information in data warehouse, acquire efficient information about how to enhance the advantages of market competition, make the concept and goal of CRM can be achieved and satisfy the demand and challenge in modern e-commerce times. It can help enterprises increase market decision-making ability, gain competitive advantages and perfect business plan.
作者机构：
[张力] Hunan Institute of Technology, Hengyang 421002, China;[Zeng, Chun; 宋明海; 彭晓春] Third Qinshan Nuclear Power Plant, Haiyan 314300, China;[赵明; 张力; 戴立操] Human Factor Institute, University of South China, Hengyang 421001, China
期刊：
International Journal of Advancements in Computing Technology,2012年4(15):371-378 ISSN：2005-8039
通讯作者：
Yi, Y.-X.(yyx19999@126.com)
作者机构：
[Liu, Meng-ya; Yi, Yong-Xi] College of Economics and Management, University of South China, China;[Li, Shou-de] Antai College of Economics and Management, Shanghai J-T University, China
通讯机构：
[Yi, Y.-X.] C;College of Economics and Management, China
摘要：
It is very important for firms who pursue profit maximization whether and when to carry on pollution abatement technology investment under tradable emissions permits and uncertainty. To consider an irreversible pollution abatement technology investment projects under a winner- takes-all patent system and the uncertainty takes two distinct forms: the technological success of the project is probabilistic, while the economic value to be won evolves stochastically over time. Considering these effects of uncertainty and using real options theory, it's to present a pollution abatement technology investment strategy option gambling model, and by analysis this model to give the best opportunity of manufacturers to carry on pollution abatement technology investment. The study shows that in pollution abatement technology investment, the pre-emptive effect damages option values to a significant degree, causing investment to take place sooner than in either the single-firm or the coordinated case.
作者机构：
[张力; 蒋建军; 皱萍萍; 李鹏程; 戴立操] Human Factors Institute, University of South China, Hengyang, Hunan, 421001, China;[张力] Hunan Technical College, Hengyang, Hunan, 421001, China;[王以群] Center for Research in Information Management, University of South China, Hengyang, Hunan, 421001, China;[彭玉元] Guangzhou Kangda Vocational Technical College, Guangzhou, 510663, China
通讯机构：
Human Factors Institute, University of South China, China
作者机构：
[Li Peng-cheng; Zhang Li; Dai Li-cao] Univ S China, Human Factor Inst, Hengyang 421001, Hunan, Peoples R China.;[Li Peng-cheng; Chen Guo-hua] S China Univ Technol, Inst Safety Sci & Engn, Guangzhou 510640, Guangdong, Peoples R China.
通讯机构：
[Li Peng-cheng] U;Univ S China, Human Factor Inst, Hengyang 421001, Hunan, Peoples R China.
关键词：
Human reliability analysis;Bayesian network;Human error;Organizational factors;Situational factors;Individual factors
摘要：
Organizational factors are the major root causes of human errors, while there have been no formal causal model of human behavior to model the effects of organizational factors on human reliability. The purpose of this paper is to develop a fuzzy Bayesian network (BN) approach to improve the quantification of organizational influences in HRA (human reliability analysis) frameworks. Firstly, a conceptual causal framework is built to analyze the causal relationships between organizational factors and human reliability or human error. Then, the probability inference model for HRA is built by combining the conceptual causal framework with BN to implement causal and diagnostic inference. Finally, a case example is presented to demonstrate the specific application of the proposed methodology. The results show that the proposed methodology of combining the conceptual causal model with BN approach can not only qualitatively model the causal relationships between organizational factors and human reliability but also can quantitatively measure human operational reliability, and identify the most likely root causes or the prioritization of root causes causing human error.
作者机构：
[周勇; 张力] Human Factor Institute, Nanhua University, Hengyang, Hunan, 421001, China;[周勇] Flight Technology College, Civil Aviation Flight University of China, Guanghan, Sichuan, 618307, China;[张力] Hunan Institute of Technology, Hengyang, Hunan, 421002, China
通讯机构：
Human Factor Institute, Nanhua University, China
期刊：
Advances in Information Sciences and Services,2012年4(17):612-619 ISSN：1976-3700
通讯作者：
Yu, Y.-C.(093008@mail.hwc.edu.tw)
作者机构：
[Yu, Yen-Chieh] Department of Accounting Information, Hsin-Wu Institute of Technology, China;[Hung, Tzu-Ying] Department of Business Administration, Nanhua University, China
通讯机构：
[Yu, Y.-C.] D;Department of Accounting Information, China
关键词：
Gap analysis;Kano model;Quality advance
摘要：
There are a lot of quality related searches enforced in practice or academic. So vary methods developed to adopt for investigation and to dig out important facts. The work applies two models are gap analysis model and Kano model. There are five gaps in the gap analysis, means customer demand or expectation that firms could not satisfy. The main idea of Kano's model is quality elements distinguished to observe the impact of customer satisfaction. Investigation object of the work is a hot spring firm. So quality attribute identified via Kano's model and how quality reformed through gap analysis in the work. Finally the work verifies quality of the hot spring firm from attractive quality attribute become one-dimensional quality attribute. To stand on observation of this study object, a new measure that the work created to grow quality for firm is success.
作者机构：
[李冬生; 李萍萍; 王纪章] Key Laboratory of Modern Agricultural Equipment and Technology, Ministry of Education and Jiangsu Provience, Jiangsu University, Zhenjiang 212013, China;[李冬生] School of Economics and Management, University of South China, Hengyang 421001, China
通讯机构：
Key Laboratory of Modern Agricultural Equipment and Technology, Ministry of Education and Jiangsu Provience, Jiangsu University, China
关键词：
A weight association rules;Dynamic function;Human factor events;SGTR
摘要：
With human factor events rising in recent years, many researches begin to pay much attention to them. Especially, human factor events in nuclear power plant show more important than other human factor events. To effectively decrease human factor events, the authors propose the method of association rule analysis of human factor events in this paper. Association rule is one of the most popular data mining techniques applied to many scientific and industrial problems. Based on traditional methods, the authors propose a weight association rule based on statistics. Weight factors consist of inner and exterior human factors. In this paper, the authors propose a dynamic function and some methods with weight in order to assess support, confidence and correlation degree among human factor events. The proposed methods are tested by experiments. From results of experiments, we can easily find higher error rate events caused by human, higher confidence and correlation degree events among human factor events of steam generator tube rupture (SGTR) of nuclear power plant (NPP). (C) 2011 Elsevier Ltd. All rights reserved.
作者机构：
[Jiang, Jian-jun] Univ S China, Human Factors Inst, Econ Management Coll, Hengyang 421001, Hunan, Peoples R China.;[Zhang, Kun; Jiang, Jian-jun] Univ S China, Coll Nucl Sci & Technol, Hengyang 421001, Hunan, Peoples R China.;[Wang, Yi-qun] Univ S China, Ctr Res Informat Management, Hengyang 421001, Hunan, Peoples R China.;[Zhang, Li] HuNan Inst Technol, Hengyang 421001, Peoples R China.;[Jiang, Jian-jun; Peng, Yu-yuan] GuangZhou KangDa Vocat Tech Coll, Dept Comp Sci, Guangzhou 511363, Guangdong, Peoples R China.
通讯机构：
[Jiang, Jian-jun] U;Univ S China, Human Factors Inst, Econ Management Coll, Hengyang 421001, Hunan, Peoples R China.
关键词：
Digital main control room;Markov model;Probability distributed function;Probability of correlation degree
摘要：
Monitoring process is an important part in a high safety digital main control room of nuclear power plant (NPP), it is the source extracted information and found abnormal information in time. As the human factors events arisen from monitoring process recently take place more and more frequent, the authors propose a reliability Markov model to effectively decrease these abnormal events. The model mainly analyzes next monitoring object probability in terms of current information and plant state. The authors divide digital human-machine interface into two parts that are referred as logical homogeneous Markov and logical heterogeneous Markov. For the former, a series of methods of probability evaluation are proposed, such as, Markov transition probability with condition, probability distributed function with human factors, system state and alarm; for the latter, the authors propose the calculation of probability of correlation degree between last time and next time and probability calculation methods with multi-father nodes. The methods can effectively estimate the transition probability from a monitoring component to next monitoring component at time t, can effectively analyze which information is more important in next monitoring process and effectively find more useful information in time t + 1, so that the human factors events in monitoring process can greatly be decreased. (C) 2011 Elsevier Ltd. All rights reserved.
作者机构：
[张力; 赵明; 李鹏程; 戴立操] Human Factor Institute, University of South China, Hengyang, Hunan, 421001, China;[陈国华; 李鹏程] Institute of Safety Science and Engineering, South China University of Technology, Guangzhou, 510641, China;[戴立操] School of Info-physics and Geomatics Engineering, Central South University, Changsha, 410083, China;[张力] Hunan Institute of Technology, Hengyang, Hunan, 421001, China
通讯机构：
Human Factor Institute, University of South China, China
