摘要：
To solve the problems of heterogeneity and disorder in the cross-domain integration processes for offsite nuclear emergency response, the integrated decision-making framework of the CDIRS spaces based on Space Mapping and Semantic Web is proposed. Under this framework, the method of feature mapping and space modeling, interoperable mediating and interoperability verifying, ordered integrating and reasoning, which are key steps of the CDIRS method, are presented. Furthermore, with a fictive nuclear accident scenario, the relevant CDIRS spaces and ordering rules are constructed, and then the appropriate cross-domain integrated response solution is obtained and verified effectively by reasoning and simulating in the CDIRS model. With the CDIRS method proposed in this paper, the heterogeneity and disorder can be avoided, and the targets and constraints of the offsite nuclear emergency response problems in the original space can be transformed into the target space, being processed unified by formal modeling and ordered reasoning. (C) 2016 Elsevier Ltd. All rights reserved.
作者机构：
[Zhang, Li; Zou, Yanhua] Univ South China, Sch Nucl Sci & Technol, Hengyang 421001, Hunan, Peoples R China.;[Zhang, Li; Zou, Yanhua] Hunan Inst Technol, Inst Human Factors Engn & Safety Management, Hengyang 421002, Hunan, Peoples R China.;[Zhang, Li; Li, Pengcheng] Univ South China, Human Factor Inst, Hengyang 421001, Hunan, Peoples R China.
通讯机构：
[Zhang, Li] H;Hunan Inst Technol, Inst Human Factors Engn & Safety Management, Hengyang 421002, Hunan, Peoples R China.
关键词：
Digital main control room;Dynamic network model;Human performance;Reliability forecasting;Situation assessment
摘要：
With the technical development of computer hardware and software, digitalization is a trend in large-scale complex systems such as nuclear power plants (NPPs). It changes the way main control room (MCR) operators interact with systems. Faced with these technical changes, operators need to continue improving their situation assessment (SA) reliability level. In addition to evaluate operators' SA reliability, managers and shift supervisors also want to forecast their SA reliability level. There have been many studies with respect to operators' SA, but most of them are static analysis method and cannot be applied to predict operators' SA reliability. So, on the basis of different forecasting approaches and observation data, how to predict the operators' SA reliability level has became a problem that many analyst interest in. In this paper, first we identified the influence factors associated with SA reliability, and then we developed the SA reliability model, finally we proposed a reliability forecasting model by integrating time series forecasting method with dynamic network model (DNM). Our experiment verification focused on steam generator tube rupture (SGTR) event, using the forecasting model, we demonstrated how to predict operators' SA reliability during the course, and the prediction results are consistent with measurement results. (C) 2015 Elsevier Ltd. All rights reserved.
期刊：
Mathematical Problems in Engineering,2015年2015 ISSN：1024-123X
通讯作者：
Zou, Qingming
作者机构：
[Zou, Qingming] Univ South China, Sch Econ & Management, Changsha 421001, Hunan, Peoples R China.;[Ye, Guangyu] S China Univ Technol, Sch Business Adm, Guangzhou 510640, Guangdong, Peoples R China.
通讯机构：
[Zou, Qingming] U;Univ South China, Sch Econ & Management, Changsha 421001, Hunan, Peoples R China.
通讯机构：
[Jiang, Jianjun] U;Univ South China, Human Factors Inst, Coll Econ & Management, Hengyang 421001, Hunan, Peoples R China.
关键词：
Digital human-computer interface;Dynamic simulative function;Human reliability;Layout of relative positions;Linear reversal genetic hybridization
摘要：
This is the first in a series of papers describing the optimal design method for a digital human-computer interface of a nuclear power plant (NPP) from three different points based on human reliability. The purpose of this series is to propose different optimization methods from varying perspectives to decrease human factor events that arise from the defects of a human computer interface. The present paper mainly discusses the optimization method for the layout of monitoring units. The layout of relative positions among different functional blocks in a digital human computer interface influences the time required to search information. The risk of an event increases with increases in the time required to search for information because of the limited time available during a nuclear emergency. To avoid the risk of such an event, the authors propose an optimization method for the layout of monitoring units based on human reliability for a digital human computer interface of a NPP. In the optimal design process, the authors propose a linear reversal genetic hybridization method that uses the Bayesian method as an adaptive function and takes human reliability as the optimized criterion. To quantitatively obtain the probability of human reliability, the authors use dynamic simulative functions including time and human factors. Finally, an experiment is conducted. The results indicate that the linear reversal genetic hybridization method has good stability and sensitivity and that the proposed optimization method has good accuracy and convergence. (C) 2015 Elsevier B.V. All rights reserved.
作者机构：
[Zhang, Li; Zou, Yanhua] Univ South China, Sch Nucl Sci & Technol, Hengyang 421001, Hunan, Peoples R China.;[Zhang, Li; Zou, Yanhua] Hunan Inst Technol, Inst Human Factors Engn & Safety Management, Hengyang 421002, Hunan, Peoples R China.;[Zhang, Li] Univ South China, Human Factor Inst, Hengyang 421001, Hunan, Peoples R China.
通讯机构：
[Zou, Yanhua] H;Hunan Inst Technol, Inst Human Factors Engn & Safety Management, Hengyang 421002, Hunan, Peoples R China.
关键词：
Boolean network;Digital main control room;Dynamic evolution;Human reliability analysis;Operators' behavior;Semi-tensor product
摘要：
Digitalization is a trend in large-scale complex systems such as nuclear power plants (NPPs). It changes the way main control room (MCR) operators interact with systems. Many studies shows that the adoption of digital technology has brought some new risks for MCR operators, and whether the reliability of these technologies can meet safety and economic requirements has become one of the urgent problems that NPPs must solve. The study consists of two parts. In Part I, we investigated the dynamic evolution of operators' four behaviors: monitoring and detection (MD), situation assessment (SA), response planning (RP), and response implementation (RI). This paper incorporates Boolean network (BN) analysis into the field of human reliability analysis (HRA), by applying semi-tensor product of matrix (STP), whereby the dynamics evolution of operators' behavior can be expressed in an algebraic form. Utilizing this algebraic representation, a BN analysis model is proposed, on which we based a qualitative analysis. An illustrative example is given to show how to construct the BN model via experimental data. We also discuss the advantage of the proposed methodology, its feasibility and highlighting the future work remaining. (C) 2015 Elsevier Ltd. All rights reserved.
关键词：
B-spline;M-estimator;Rate of convergence;Single-index model
摘要：
The single-index model is an important tool in multivariate nonparametric regression. This paper deals with M-estimators for the single-index model. Unlike the existing M-estimator for the single-index model, the unknown link function is approximated by B-spline and M-estimators for the parameter and the nonparametric component are obtained in one step. The proposed M-estimator of unknown function is shown to attain the convergence rate as that of the optimal global rate of convergence of estimators for nonparametric regression according to Stone (Ann Stat 8:1348–1360, 1980; Ann Stat 10:1040–1053, 1982), and the M-estimator of parameter is
$$\sqrt{n}$$
-consistent and asymptotically normal. A small sample simulation study showed that the M-estimators proposed in this paper are robust. An application to real data illustrates the estimator’s usefulness.
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.
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：
[Zhang Li; Dai Licao; Li Pengcheng] Univ S China, Human Factor Inst, Hengyang 421001, Peoples R China.;[Dai Licao] Cent S Univ, Sch Infophys & Geomat Engn, Changsha 410083, Hunan, Peoples R China.;[Zhang Li] Hunan Inst Technol, Hengyang 421003, Peoples R China.
通讯机构：
[Dai Licao] U;Univ S China, Human Factor Inst, Hengyang 421001, Peoples R China.
关键词：
THERP plus HCR;HCR data modification;HRA event tree;Case study
摘要：
Human reliability analysis (HRA) is generally viewed as quite an important part in probabilistic safety assessment (PSA). In this paper, a THERP + HCR HRA model is presented to model the operators' post-accident behavior in Chinese nuclear power plants. The paper shows how the model is structured and how to consider and acquire the corresponding data, including HCR data modification and HRA event tree data. A case study is presented to make an illustration. (C) 2010 Elsevier Ltd. All rights reserved.
摘要：
In the system reliability and safety assessment, the focuses are not only the risks caused by hardware or software, but also the risks caused by "human error". There are uncertainties in the traditional human error risk assessment (e.g. HECA) due to the uncertainties and imprecisions in Human Error Probability (HEP), Error-Effect Probability (EEP) and Error Consequence Severity (ECS). While fuzzy logic can deal with uncertainty and imprecision. It is an efficient tool for solving problems where knowledge uncertainty may occur. The purpose of this paper is to develop a new Fuzzy Human Error Risk Assessment Methodology (FHERAM) for determining Human Error Risk Importance (HERI) as a function of HEP, EEP and ECS. The modeling technique is based on the concept of fuzzy logic, which offers a convenient way of representing the relationships between the inputs (i.e. HEP, EEP, and ECS) and outputs (i.e. HERI) of a risk assessment system in the form of IF THEN rules. It is implemented on fuzzy logic toolbox of MATLAB using Mamdani techniques. A case example is presented to demonstrate the proposed approach. Results show that the method is more realistic than the traditional ones, and it is practicable and valuable. (C) 2010 Elsevier Ltd. All rights reserved.
摘要：
We consider the dynamical properties for a kind of fourth-order rational difference equations. The key is for us to find that the successive lengths of positive and negative semicycles for nontrivial solutions of this equation periodically occur with same prime period 5. Although the period is same, the order for the successive lengths of positive and negative semicycles is completely different. The rule is ..., 3+, 2-, 3+, 2-, 3+, 2-, 3+, 2-,..., or ..., 2+, 1-, 1+, 1-, 2+, 1-, 1+, 1-,..., or ..., 1+, 4-, 1+, 4-, 1+, 4-, 1+, 4-,... By the use of the rule, the positive equilibrium point of this equation is proved to be globally asymptotically stable.
摘要：
This paper explores the factors affecting project competence within firms producing complex products and systems (CoPS). We developed a research framework for the analysis of factors affecting the project competence in CoPS. Literature review and Nominal Group Technique were used to identify these factors and to assist in developing a questionnaire to identify and rank their associated measured variables, five key factors were identified and extracted by using factor analysis, and these resulting factors were related to the overall project competence in CoPS by using a multiple regression analysis method, then the results of factor analysis and multiple regression analysis were valuated and confirmed by using structural equation modeling, in which corresponding tentative model was constructed and tested quantitatively. The proposed model identified five building blocks of project competence in CoPS, namely project environment, technology, innovation, organization management and operation process. The paper argues that these firms are only able to effectively harness and reproduce their project competence by integrating these five building blocks within the firm.
摘要：
The local influence analysis is an important problem in statistical inference and some models have been discussed in many literatures[1- 5]. This paper deals with the problem of assessing local influences in a multivariate t-model with Rao's simple structure(RSS). Based on Cook's likelihood displacement, the effects of some minor perturbation on the statistical inference is assessed. As an application, a common covariance-weighted perturbation is thoroughly discussed.
