期刊：
Statistics in Medicine,2012年31(7):681-697 ISSN：1097-0258
通讯作者：
Li, Xiao-Song
作者机构：
[Feng, Ping] Sichuan Univ, W China Hosp, Inst Clin Trials, Chengdu, Sichuan, Peoples R China.;[Li, Xiao-Song] Sichuan Univ, W China Sch Publ Hlth, Chengdu, Sichuan, Peoples R China.;[Zhou, Xiao-Hua] Harbin Med Coll, Harbin, Peoples R China.;[Zhou, Xiao-Hua] Univ Washington, Sch Publ Hlth, Dept Biostat, Seattle, WA 98195 USA.;[Zhou, Xiao-Hua] Peking Univ, Beijing Int Ctr Math Res, Beijing 100871, Peoples R China.
通讯机构：
[Li, Xiao-Song] Sichuan Univ, W China Sch Publ Hlth, Chengdu, Sichuan, Peoples R China.
关键词：
causal inference<&wdkj&>generalized propensity score<&wdkj&>treatment effect<&wdkj&>Traditional Chinese Medicine (TCM)<&wdkj&>multiple treatment components
摘要：
The propensity score method is widely used in clinical studies to estimate the effect of a treatment with two levels on patient's outcomes. However, due to the complexity of many diseases, an effective treatment often involves multiple components. For example, in the practice of Traditional Chinese Medicine (TCM), an effective treatment may include multiple components, e.g. Chinese herbs, acupuncture, and massage therapy. In clinical trials involving TCM, patients could be randomly assigned to either the treatment or control group, but they or their doctors may make different choices about which treatment component to use. As a result, treatment components are not randomly assigned. Rosenbaum and Rubin proposed the propensity score method for binary treatments, and Imbens extended their work to multiple treatments. These authors defined the generalized propensity score as the conditional probability of receiving a particular level of the treatment given the pre-treatment variables. In the present work, we adopted this approach and developed a statistical methodology based on the generalized propensity score in order to estimate treatment effects in the case of multiple treatments. Two methods were discussed and compared: propensity score regression adjustment and propensity score weighting. We used these methods to assess the relative effectiveness of individual treatments in the multiple-treatment IMPACT clinical trial. The results reveal that both methods perform well when the sample size is moderate or large. Copyright (c) 2011 John Wiley & Sons, Ltd.
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] Univ S China, Human Factor Inst, Hengyang 421001, Hunan, Peoples R China.
关键词：
Human reliability analysis<&wdkj&>Bayesian network<&wdkj&>Human error<&wdkj&>Organizational factors<&wdkj&>Situational factors<&wdkj&>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.
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.
作者：
Li Peng-cheng*;Zhang Li;Dai Li-cao;Li Xiao-fang
期刊：
Annals of Nuclear Energy,2017年102:168-178 ISSN：0306-4549
通讯作者：
Li Peng-cheng
作者机构：
[Li Peng-cheng; Zhang Li; Dai Li-cao; Li Xiao-fang] Univ South China, Human Factor Inst, Hengyang 421001, Hunan, Peoples R China.;[Li Peng-cheng] Univ South China, Sch Nucl Sci & Technol, Hengyang 421001, Hunan, Peoples R China.
通讯机构：
[Li Peng-cheng] Univ South China, Human Factor Inst, Hengyang 421001, Hunan, Peoples R China.
关键词：
Situation awareness<&wdkj&>Human error<&wdkj&>Analysis method<&wdkj&>Digitized main control rooms
摘要：
Situation awareness (SA) is a key element that impacts operator's decision-making and performance in nuclear power plants (NPPs). The subsequent complex cognitive activities cannot be correctly completed due to errors of situation awareness (ESA), which will lead to disastrous consequences. In order to investigate and analyze operator's ESA in the digitized main control room (DMCR) of a nuclear power plant, the model of ESA is established, the classification system of ESA is developed based on the built ESA model, and the analysis method of ESA is also constructed on the basis of the observation of simulator and operator surveys. Finally, a case study is provided to illustrate the concrete application of the method. It provides a theoretical and practical support for the operator's SAE analysis in a digitized main control room of a nuclear power plant. (C) 2016 Elsevier Ltd. All rights reserved.
作者：
Zou, Yanhua*;Zhang, Li;Dai, Licao;Li, Pengcheng;Qing, Tao
期刊：
Nuclear Engineering and Technology,2017年49(2):335-341 ISSN：1738-5733
通讯作者：
Zou, Yanhua
作者机构：
[Zhang, Li; Zou, Yanhua] Hunan Inst Technol, Inst Human Factors Engn & Safety Management, Hengyang, Hunan, Peoples R China.;[Qing, Tao; Li, Pengcheng; Dai, Licao] Univ South China, Human Factors Inst, Hengyang, Hunan, Peoples R China.
通讯机构：
[Zou, Yanhua] Hunan Inst Technol, Inst Human Factors Engn & Safety Management, Hengyang, Hunan, Peoples R China.
会议名称：
13th International Conference on Probabilistic Safety Assessment and Management (PSAM)
会议时间：
OCT 02-07, 2016
会议地点：
Seoul, SOUTH KOREA
会议主办单位：
[Zou, Yanhua;Zhang, Li] Hunan Inst Technol, Inst Human Factors Engn & Safety Management, Hengyang, Hunan, Peoples R China.^[Dai, Licao;Li, Pengcheng;Qing, Tao] Univ South China, Human Factors Inst, Hengyang, Hunan, Peoples R China.
关键词：
Digital Control System;Human Reliability Analysis;Nuclear Power Plant
摘要：
The main control room (MCR) in advanced nuclear power plants (NPPs) has changed from analog to digital control system (DCS). Operation and control have become more automated, centralized, and accurate due to the digitalization of NPPs, which has improved the efficiency and security of the system. New issues associated with human reliability inevitably arise due to the adoption of new accident procedures and digitalization of main control rooms in NPPs. The LingAo II NPP is the first digital NPP in China to apply the stateoriented procedure. In order to address issues related to human reliability analysis for DCS and DCS + state-oriented procedure, the Hunan Institute of Technology conducted a research project based on a cooperative agreement with the LingDong Nuclear Power Co. Ltd. This paper is a brief introduction to the project. Copyright (C) 2017, Published by Elsevier Korea LLC on behalf of Korean Nuclear Society.
摘要：
This paper proposes a novel H∞ tracking-based decentralized hybrid adaptive fuzzy controller via output feedback for a class of large-scale uncertain nonlinear systems. To achieve better adaptation properties, the proposed controller is a weighted combination of indirect and direct adaptive fuzzy controls (IAFC and DAFC) such that both fuzzy descriptions and control rules can be incorporated at the same time. After proper filtering of the observation error dynamics, the developed observer-based feedback and adaptation mechanisms become implementable indeed. By using fuzzy inference systems, a state observer and H∞ tracking technique, the decentralized combined indirect and direct adaptive fuzzy control algorithm is developed based upon a united H∞ tracking controller design for the modification of the previous work of Huang et al. The resultant closed-loop systems are guaranteed to be stable and a good H∞ tracking performance is obtained. Simulation results of interrelated inverted pendulums substantiate that the proposed CAFC system stands out as being better properties than typical IAFC and DAFC systems in that the tracking performance is much better while the control effort is even smaller.
期刊：
Mathematical Problems in Engineering,2015年2015 ISSN：1024-123X
通讯作者：
Zou, QM
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, QM ] Univ South China, Sch Econ & Management, Changsha 421001, Hunan, Peoples R China.;Univ South China, Sch Econ & Management, Changsha 421001, Hunan, Peoples R China.
作者机构：
[Li, Pengcheng; Zhang, Li; Li, Xiaofang; Dai, Licao] Univ South China, Human Factor Inst, Hengyang 421001, Hunan, Peoples R China.;[Li, Pengcheng] Univ N Carolina, Syst Engn & Engn Management, Charlotte, NC 28223 USA.;[Li, Pengcheng] Univ South China, Sch Nucl Sci & Technol, Hengyang 421001, Hunan, Peoples R China.;[Zou, Yanhua] Hunan Inst Technol, Inst Human Factor & Safety Management, Hengyang 421002, Hunan, Peoples R China.
通讯机构：
[Li, Pengcheng] Univ South China, Human Factor Inst, Hengyang 421001, Hunan, Peoples R China.
关键词：
Situation awareness reliability<&wdkj&>Fuzzy logic<&wdkj&>Analytic hierarchy process<&wdkj&>Digital nuclear power plants
摘要：
In digital control rooms, situation awareness (SA) reliability has become an important element affecting operator's reliability. In order to establish a more reasonable assessment method of SA reliability under the condition of very lack of data, based on the established influential factor model of SA reliability considering the causality relationship of performance shaping factors (PSFs) in this paper, a fuzzy logic and analytic hierarchy process (AHP)-based method is established to more objectively assess SA reliability. The weight of PSFs is identified using AHP, and a fuzzy logic method is used to simulate the fuzzy assessment and reasoning process of operator's SA reliability, and a standardized method is built to determine the fuzzy rule base of fuzzy reasoning system for SA reliability assessment for reducing the subjectivity and uncertainty of expert judgment. Finally, an example is provided to illustrate the specific application of the proposed method. The results show that the established method takes account of the weight of PSFs and their causal influencing relationship, and the fuzzy logic method used to assess SA reliability can overcome the subjectivity and uncertainty of expert judgment, which makes the assessment results more objective and realistic. Furthermore, the method can be used to get more SA error data and have a wide range of application value.
通讯机构：
[Jiang, Jianjun] Univ South China, Human Factors Inst, Coll Econ & Management, Hengyang 421001, Hunan, Peoples R China.
关键词：
Digital human–computer interface<&wdkj&>Layout of relative positions<&wdkj&>Linear reversal genetic hybridization<&wdkj&>Human reliability<&wdkj&>Dynamic simulative function
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.
作者机构：
[Li, Pengcheng; Zhang, Li; Li, Xiaofang; Dai, Licao] Univ South China, Human Factor Inst, Hengyang 421001, Hunan, Peoples R China.;[Li, Pengcheng] Univ N Carolina, Syst Engn & Engn Management, Charlotte, NC 28223 USA.;[Li, Pengcheng] Univ South China, Sch Nucl Sci & Technol, Hengyang 421001, Hunan, Peoples R China.
通讯机构：
[Dai, Licao] Univ South China, Human Factor Inst, Hengyang 421001, Hunan, Peoples R China.
关键词：
Model validation<&wdkj&>Simulation experiment<&wdkj&>SA reliability<&wdkj&>Fuzzy logic-AHP<&wdkj&>Digital nuclear power plants
摘要：
Situation awareness (SA) reliability of operators is an important component of human reliability analysis (HRA) in digital nuclear power plants (NPPs). Therefore, how to identify effectively and reliably the risk of SA errors is of great significance for SA error prevention and risk reduction. SA reliability assessment model or method based on fuzzy logic and analytic hierarchy process (AHP) is forwarded in the first paper. In order to prove its effectiveness and reliability, sensitivity analysis and simulator experiments are applied to testify our model in this paper. The results show that the proposed assessment model of SA reliability has a certain degree of sensitivity as well as an accuracy of prediction, and there are a strong correlation and consistency between the predicted value from fuzzy inference system and the real value (or observed value) from simulator experiments. Although there are some differences between the predicted value and the real value based on the perspective of HRA, the model can be used to predict SA error probability or SA reliability within the range of 10 error factors as well as provide data and theoretical support for SA reliability assessment.
期刊：
Annals of Nuclear Energy,2018年120:48-61 ISSN：0306-4549
通讯作者：
Li, Peng-cheng
作者机构：
[Li, Xiao-fang; Li, Peng-cheng; Zhang, Li; Dai, Li-cao; Jiang, Yu] Univ South China, Human Factor Inst, Hengyang 421001, Hunan, Peoples R China.;[Li, Peng-cheng] Univ North Carolina Charlotte, Syst Engn & Engn Management, Charlotte, NC 28223 USA.;[Li, Peng-cheng] Univ South China, Sch Nucl Sci & Technol, Hengyang 421001, Hunan, Peoples R China.;[Zhang, Li] Hunan Inst Technol, Inst Human Factor & Safety Management, Hengyang 421002, Hunan, Peoples R China.
通讯机构：
[Li, Peng-cheng] Univ South China, Human Factor Inst, Hengyang 421001, Hunan, Peoples R China.
关键词：
Human error analysis<&wdkj&>Organizational root cause<&wdkj&>Human errors<&wdkj&>Performance shaping factors<&wdkj&>Digital nuclear power plants
摘要：
In nuclear power plants (NPPs), man-machine interfaces (MMIs) are being transformed from conventional panels to computer workstations. Therefore, operators' behavior and performance shaping factors (PSFs) in modern main control rooms (MCRs) differs from what they do in a conventional one. New human error, error mechanism and PSFs etc. are introduced into digital control systems (DCS). The conventional human error analysis (HEA) methods cannot meet new requirements. So it is important to establish a new technique of HEA for investigating human failure events in digital NPPs. In order to investigate and analyze human errors and to trace organizational root causes in digital NPPs, an Organization oriented Technique of Human Error Analysis (OTHEA) was established. At this first paper, an organization-oriented conceptual model of HEA was established. Furthermore, the classification framework of HEA was developed based on the established conceptual model of HEA, including classification of human error, PSFs, psychological error mechanisms (PEMs), error recovery failures (ERFs) and safety barriers. It provides a theoretical guidance and practical support for the investigation of human failure events in digital NPPs. (C) 2018 Elsevier Ltd. All rights reserved.
期刊：
Annals of Nuclear Energy,2017年106:247-255 ISSN：0306-4549
通讯作者：
Jiang, Jianjun
作者机构：
[Jiang, Jianjun; Zhang, Li] Hunan Inst Technol, Sch Safety & Environm Engn, Hengyang 421002, Hunan, Peoples R China.;[Jiang, Jianjun; Wang, Yiqun; Zhang, Mengjia; Xie, Tian] Univ South China, Sch Econ & Management, Human Factors Inst, Hengyang 421001, Hunan, Peoples R China.;[Li, Min; Wu, Daqing] Univ South China, Sch Comp Sci & Technol, Hengyang 421001, Hunan, Peoples R China.;[Peng, Yuyuan] South China Univ Technol, Guangzhou Coll, Sch Comp Engn, Guangzhou 510830, Guangdong, Peoples R China.;[Peng, Jie] GuangDong Univ Finance & Econ, Informat Sci Coll, Guangzhou 510320, Guangdong, Peoples R China.
通讯机构：
[Jiang, Jianjun] Hunan Inst Technol, Sch Safety & Environm Engn, Hengyang 421002, Hunan, Peoples R China.;[Jiang, Jianjun] Univ South China, Sch Econ & Management, Human Factors Inst, Hengyang 421001, Hunan, Peoples R China.
关键词：
Human reliability<&wdkj&>Quantity of components<&wdkj&>Quick convergence search method<&wdkj&>Affinity error probability mapping function
摘要：
This is the second in a series of papers describing the optimal design method for a digital human computer interface of nuclear power plant (Npp) from three different points based on human reliability. The purpose of this series is to explore different optimization methods from varying perspectives. This present paper mainly discusses the optimal design method for quantity of components of the same factor. In monitoring process, quantity of components has brought heavy burden to operators, thus, human errors are easily triggered. To solve the problem, the authors propose an optimization process, a quick convergence search method and an affinity error probability mapping function. Two balanceable parameter values of the affinity error probability function are obtained by experiments. The experimental results show that the affinity error probability mapping function about human-computer interface has very good sensitivity and stability, and that quick convergence search method for fuzzy segments divided by component quantity has better performance than general algorithm. (C) 2017 Elsevier Ltd. All rights reserved.
作者机构：
[Zhang, Ying; Zhang, Caiping] Univ South China, Sch Econ & Management, Hengyang, Peoples R China.;[Randhir, Timothy O.] Univ Massachusetts, Dept Environm Conservat, Amherst, MA 01003 USA.
通讯机构：
[Randhir, Timothy O.] Univ Massachusetts, Dept Environm Conservat, Amherst, MA 01003 USA.
关键词：
low-carbon transformation<&wdkj&>carbon assets<&wdkj&>indicator management method<&wdkj&>indicator system
摘要：
Effective carbon asset management is necessary for decreasing carbon resource inputs and reducing carbon emission. Furthermore, carbon asset management is an important measure to realize low-carbon transformation and low-carbon competitiveness for enterprises. However, a systematic theoretical framework and an effective management method for carbon asset management are lacking. Therefore, the paper defines carbon assets as tangible and intangible assets that can help reduce carbon emission and create low-carbon value based on the essence of carbon resources. In order to demonstrate a carbon asset's positive role in reducing carbon emission, the paper constructs carbon asset management indicators including carbon fund turnover ratio, carbon emission rate, carbon turnover ratio, carbon technology transformation efficiency and fixed carbon asset profitability. The carbon asset management practice of Bao Steel Corporation shows that the indicator system can accurately reflect the efficiency and effect of carbon asset management. That is, carbon fund turnover ratio can reflect a carbon fund's utilization efficiency; carbon emission rate reflects the carbon materials’ different effects on carbon emission; carbon turnover ratio reflects the profit of carbon trading; fixed carbon asset profitability reflects the low-carbon earning power to some degree; and carbon technology transformation efficiency reflects the maturity of low-carbon technology. However, with carbon asset management in the forefront of the carbon accounting field, some issues, including the nature of the carbon asset, management pattern and comparative analysis of more cases, need to be explored in future research to deepen the understanding of the essence of carbon asset management.
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.
