Fuzzy Cognition on Factors Influencing the Co-Branding in Technical Standards Alliance – From Member Selection Perspective

2017 ◽  
Vol 21 (6) ◽  
pp. 1065-1072
Author(s):  
Jing Hu ◽  
◽  
Mingshun Song ◽  
Xiao Yu
Keyword(s):  
Influencing Factors ◽  
Hebbian Learning ◽  
Learning Algorithm ◽  
Evaluation Model ◽  
Influential Factors ◽  
Fuzzy Cognitive Map ◽  
Fuzzy Evaluation ◽  
Technical Standards ◽  
Member Selection ◽  
Mutual Relations

Branding is an important resource in a technical standards alliance. As a kind of essential resource utilization pattern, joint branding is beneficial for the enterprises in an alliance in realizing the increment of value. The selection of a cooperative partner is the first step in co-branding, and plays a significant role. This paper emphasizes the critical significance of alliance member selection for co-branding, and regards it as a breakthrough point in analyzing the key influential factors and causal correlation of such branding. Through a combination of a fuzzy cognitive map and the non-linear Hebbian learning algorithm, this research establishes a fuzzy evaluation model, realizes the dynamic simulation of a complex network system with multiple causal correlations, and obtains a final steady state of co-branding for a technical standards alliance. Thus, it allows a better understanding of the mutual relations among the different influencing factors of co-branding and their effect, as well as the proposal of a reference policy for an improvement of such influencing factors and the conversion efficiency of the optimal results.

Fuzzy Cognitive Research on Factors Influencing Technological Innovation – From Path Dependence Perspective

2016 ◽  
Vol 20 (4) ◽  
pp. 543-553
Author(s):  
Jing Hu ◽  
◽  
Yong Zhang ◽  
Yilin Wang ◽  
Keyword(s):  
Technological Innovation ◽  
Path Dependence ◽  
Hebbian Learning ◽  
Learning Algorithm ◽  
Computer Software ◽  
Feedback System ◽  
Cognitive Map ◽  
Fuzzy Cognitive Map ◽  
Innovation Activity ◽  
Stable Conditions

This paper aims to establish a framework for evaluating technological innovation and to emphasize the important influence of path dependence on technological innovation. The fuzzy cognitive map (FCM) method is used to identify causal relationships among factors that influence technological innovation, and a FCM structural diagram for evaluating enterprise technological innovation is described. Meanwhile, a fuzzy feedback system for the evaluation of technological innovation, integrated with a nonlinear Hebbian learning algorithm, is established; dependence on expert opinions may be avoided through learning and practice using the cognitive map. Finally, using a computer software platform, a dynamic simulation of any complex index system can be realized. From this simulation, stable conditions can provide path references by which an enterprise engaging in technological innovation can improve the integrative efficiency and the overall effect of any realistic technological innovation activity.

scholarly journals Comparative Analysis of Risk Assessment for Technical Standards Alliance Based on BP Neural Network and Fuzzy AHP Methods

2018 ◽  
Vol 22 (6) ◽  
pp. 838-845 ◽  
Author(s):  
Jing Hu ◽  
Lijun Zhou ◽  
Yilin Wang ◽  
◽  
Keyword(s):  
Neural Network ◽  
Strategic Alliances ◽  
Fuzzy Ahp ◽  
Evaluation Model ◽  
Back Propagation ◽  
Fuzzy Evaluation ◽  
Technical Standards ◽  
Core Technology ◽  
Evaluation Models ◽  
Leading Enterprises

Establishing unified industrial technical standards for a single enterprise in a highly global integrated market is becoming increasingly difficult. In recent years, leading enterprises have often built technical standards alliances around a key core technology to develop industrial standards cooperatively in order to learn from each other and optimize their resource allocation. Although such technical standards alliances result in huge gains to their members, their internal and external risks threaten both the alliances and their members. As compared to other forms of strategic alliances, the risk of such an alliance has fuzzy characteristics and is difficult to fully and accurately identify. This paper uses a fuzzy pattern-recognition method to evaluate and summarize the risks of technical standards alliances. A fuzzy analytic hierarchy process (AHP) evaluation and back propagation (BP) logic fuzzy neural network methods are used to construct a risk-evaluation model of technical standards alliances while considering an alliance around new-energy automobiles in Zhejiang as an empirical example. The two evaluation models are then contrastively analyzed, and cross validation of the evaluation results is performed in order to provide theoretical guidance and support for the application of two fuzzy evaluation models in practice.

Fuzzy comprehensive evaluation model for construction risk analysis in urban subway

2015 ◽  
Vol 06 (03) ◽  
pp. 1550024
Author(s):  
Chun-Quan Dai ◽  
Zeng-Hui Zhao
Keyword(s):  
Evaluation Method ◽  
Comprehensive Evaluation ◽  
Evaluation Model ◽  
Fuzzy Comprehensive Evaluation ◽  
Influential Factors ◽  
Fuzzy Membership Function ◽  
Fuzzy Evaluation ◽  
Analytic Hierarchy ◽  
Construction Risk ◽  
Evaluation Matrix

On the basis of expert questionnaire and the relevant specification, multi-factors influencing weight matrix was constructed by Analytic Hierarchy Process (AHP) improved in transfer matrix algorithm, and influential factors were fuzzy classified to construct the fuzzy evaluation matrix by using trapezoidal fuzzy membership function. Fuzzy evaluation analysis was carried out through multistage fuzzy comprehensive evaluation method, and verified in combination with engineering construction condition of shallow buried tunnel with large span of Zhongshan Park Station in Qingdao Metro, and four kinds of risk control schemes were established and compared on the analysis of tunnel construction risk. Results show that the model was feasible and the improved construction scheme was very effective to reduce the construction risk.

A fuzzy evaluation method of road vehicle automatic weighing instrument in dynamic force metrological performance

2020 ◽  
Vol 64 (1-4) ◽  
pp. 1365-1372
Author(s):  
Xiaohui Mao ◽  
Liping Fei ◽  
Xianping Shang ◽  
Jie Chen ◽  
Zhihao Zhao
Keyword(s):  
Evaluation Method ◽  
Comprehensive Evaluation ◽  
Evaluation Model ◽  
Dynamic Performance ◽  
Dynamic Force ◽  
Fuzzy Evaluation ◽  
Road Vehicle ◽  
Evaluation Standard ◽  
The Road ◽  
Metrological Performance

The measurement performance of road vehicle automatic weighing instrument installed on highways is directly related to the safety of roads and bridges. The fuzzy number indicates that the uncertain quantization problem has obvious advantages. By analyzing the factors affecting the metrological performance of the road vehicle automatic weighing instrument, combined with the fuzzy mathematics theory, the weight evaluation model of the dynamic performance evaluation of the road vehicle automatic weighing instrument is proposed. The factors of measurement performance are summarized and calculated, and the comprehensive evaluation standard of the metering performance of the weighing equipment is obtained, so as to realize the quantifiable analysis and evaluation of the metering performance of the dynamic road vehicle automatic weighing instrument in use, and provide data reference for adopting a more scientific measurement supervision method.

scholarly journals Fuzzy Evaluation Model of Process Improvement Capability with Costs Consideration

2021 ◽  
Vol 11 (10) ◽  
pp. 4344
Author(s):  
Kuen-Suan Chen ◽  
Shui-Chuan Chen ◽  
Ting-Hsin Hsu ◽  
Min-Yi Lin ◽  
Chih-Feng Wu
Keyword(s):  
Process Improvement ◽  
Quality Evaluation ◽  
Evaluation Model ◽  
Fuzzy Evaluation ◽  
Sampling Errors ◽  
Capability Index ◽  
Testing Method ◽  
Improvement Potential ◽  
Testing Accuracy

The Taguchi capability index, which reflects the expected loss and the yield of a process, is a useful index for evaluating the quality of a process. Several scholars have proposed a process improvement capability index based on the expected value of the Taguchi loss function as well as the corresponding cost of process improvement. There have been a number of studies using the Taguchi capability index to develop suppliers’ process quality evaluation models, whereas models for evaluating suppliers’ process improvement potential have been relatively lacking. Thus, this study applies the process improvement capability index to develop an evaluation model of the supplier’s process improvement capability, which can be provided to the industry for application. Besides, owing to the current need to respond quickly, coupled with cost considerations and the limits of technical capabilities, the sample size for sampling testing is usually not large. Consequently, the evaluation model of the process improvement capability developed in this study adopts a fuzzy testing method based on the confidence interval. This method reduces the risk of misjudgment due to sampling errors and improves the testing accuracy because it can incorporate experts and their accumulated experiences.

scholarly journals Knowledge, attitudes, practices, and influencing factors of anxiety among pregnant women in Wuhan during the outbreak of COVID-19: a cross-sectional study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Wenping Ding ◽  
Jianmei Lu ◽  
Yan Zhou ◽  
Weizhong Wei ◽  
Zhihong Zhou ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Pregnant Women ◽  
Influencing Factors ◽  
Information Source ◽  
Influential Factors ◽  
Public Health Issue ◽  
Cross Sectional ◽  
Factors Associated ◽  
Attitudes And Practices ◽  
Prenatal Anxiety

Abstract Background Prenatal anxiety has been a significant public health issue globally, leading to adverse health outcomes for mothers and children. The study aimed to evaluate the sociodemographic characteristics, knowledge, attitudes, and practices (KAP), and anxiety level of pregnant women during the coronavirus disease 2019 (COVID-19) epidemic in Wuhan and investigate the influencing factors for prenatal anxiety in this specific context. Methods Pregnant subjects’ KAP towards COVID-19 and their sociodemographics and pregnancy information were collected using questionnaires. The Zung Self-Rating Anxiety Scale (SAS) was used to assess anxiety status. Factors associated with the level of prenatal anxiety were analyzed by Pearson’s chi-square test and multivariable logistic regression analyses. Results The prenatal anxiety prevalence in this population was 20.8%. The mean score of knowledge was 13.2 ± 1.1 on a 0 ~ 14 scale. The attitudes and practices data showed that 580/ 817 (71.0%) were very concerned about the news of COVID-19, 455/817 (55.7%) considered the official media to be the most reliable information source for COVID-19, and 681/817 (83.4%) were anxious about the possibility of being infected by COVID-19. However, only 83/817 (10.2%) worried about contracting COVID-19 infection through the ultrasound transducer during a routing morphology scan. About two-thirds 528/817 (64.6%) delayed or canceled the antenatal visits. Approximately half of them 410/817 (50.2%) used two kinds of personal protection equipments (PPEs) during hospital visits. Logistic regression analysis revealed that the influential factors for prenatal anxiety included previous children in the family, knowledge score, media trust, worry of contracting the COVID-19 infection and worry about getting infected with COVID-19 from the ultrasound probe antenatal care (ANC) schedule. Conclusion Prenatal anxiety was prevalent among pregnant women in Wuhan during the outbreak of COVID-19. The current findings identified factors associated with the level of prenatal anxiety that could be targeted for psychological care.

scholarly journals Developing a Novel Fuzzy Evaluation Model by One-Sided Specification Capability Indices

Mathematics ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 1076
Author(s):  
Wei Lo ◽  
Chun-Ming Yang ◽  
Kuei-Kuei Lai ◽  
Shao-Yu Li ◽  
Chi-Han Chen
Keyword(s):  
Evaluation Model ◽  
Critical Value ◽  
Process Quality ◽  
Quality Characteristic ◽  
Fuzzy Membership Function ◽  
Environmental Damage ◽  
Quality Level ◽  
Fuzzy Evaluation ◽  
Radar Chart ◽  
Fuzzy Evaluation Model

When all of the one-sided specification indices of each quality characteristic reach the requirements of the process quality level, they can ensure that the process capability of the product meets the requirements of the process quality level. This study constructs a fuzzy membership function based on the upper confidence limit of the index, derives the fuzzy critical value, and then labels the fuzzy critical value on the axis of the visualized radar chart as well as connects adjacent critical points to shape a regular polygonal critical region. Next, this study calculates the observed value of the index to estimate and mark it on the axis for forming a visualized fuzzy radar evaluation chart. Obviously, this fuzzy evaluation model not only reduces the testing cost but also makes the quality level quickly meet the requirements of the specifications. Further, the radar chart can reduce the risk of misjudgment attributable to sampling errors and help improve the accuracy of evaluation by a confidence-upper-limit-based fuzzy evaluation model. Therefore, this easy-to-use visualized fuzzy radar evaluation chart is used as an evaluation interface, which has good and convenient management performance to identify and improve critical-to-quality quickly. Improving the quality of the process before the product is completed will also have the advantage of reducing social losses and environmental damage costs.

scholarly journals Effect of Curriculum Planning for Physical Education in Colleges on Innovation Ability

2020 ◽  
Vol 15 (12) ◽  
pp. 103
Author(s):  
Huiqiu Guo
Keyword(s):  
Physical Education ◽  
Fuzzy Theory ◽  
Evaluation Model ◽  
Curriculum Planning ◽  
Practical Significance ◽  
Fuzzy Evaluation ◽  
Promoting Effect ◽  
Innovation Ability ◽  
Fuzzy Evaluation Model ◽  
Current Curriculum

With poor integrity and unclear goals, the curriculum planning for physical education (PE) in colleges cannot effectively promote the innovation ability of students. To solve the problem, this paper attempts to clearly evaluate the effect of curriculum planning for college PE on the innovation ability of PE majors. Based on the defects of the current curriculum planning, the authors put forward several strategies and suggestions to enhance the promoting effect of college PE curriculum planning on innovation ability. Following the fuzzy theory, an index system and a fuzzy evaluation model were put forward to quantify the effect of college PE curriculum planning on innovation ability. The research results have great theoretical and practical significance.

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