Process system failure evaluation method based on a Noisy-OR gate intuitionistic fuzzy Bayesian network in an uncertain environment

Author(s):  
Yu Jianxing ◽  
Wu Shibo ◽  
Yu Yang ◽  
Chen Haicheng ◽  
Fan Haizhao ◽  
...  
2020 ◽  
Vol 39 (2) ◽  
pp. 1515-1523
Author(s):  
Xie Lechen ◽  
Wang Wenlan

In order to enhance the risk investment evaluation algorithm precision of forestry rights mortgage of farmers, this paper provides a method of risk investment validating process of forestry rights mortgage of farmers based on dynamic Bayes network (DBN) and fuzzy system. For that have to be processed fuzzy data in time arrangement and evaluate the circumstance viably, Intuitionistic Fuzzy Dynamic Bayesian Network (IFDBN) is assembled. Intuitionistic fuzzy thinking is implanted into DBN as a virtual node in this method. Also, another technique to change over the intuitionistic fuzzy thinking yield into likelihood that could contribution to DBN as proof is proposed. Firstly, it analyzes the risk investment of forestry rights mortgage of farmers, raises the risk evaluation system and adopts normalization and factor analysis methods to pre-process the model index; secondly, by aid of a four-layer DBN model, it puts forward the hierarchical DBN model of risk investment, having input layer, fuzzy layer, fuzzy inference layer and output layer, designs the composition and calculation mode of fuzzy function module and DBN module; Finally, it verifies the viability of the calculation through experimental examination.


Author(s):  
Hao Xu ◽  
Liuxin Chen ◽  
Qiongfang Li ◽  
Jianchao Yang

Due to the continuous changes of political environment, consumption habits, technological progress and other factors, the external environment of enterprises is full of uncertainty. The turbulence of external environment is not conducive to the long-term operation and development of enterprises, but also brings great challenges to the selection of suppliers. This makes the competition of enterprises focus on how to choose long-term cooperation suppliers in the uncertain external environment. In addition, due to the deterioration of the global environment, governments pay more and more attention to environmental pollution, and consumers are more and more inclined to green consumption, which makes many companies pay more and more attention to environmental indicators when selecting suppliers. In the case of external environment turbulence and serious environmental pollution, the evaluation and selection of green suppliers in uncertain environment is particularly important for the long-term development of enterprises. What’s more, when the supplier’s capability gap is small, the decision-maker often hesitates among several suppliers. In this paper, the hesitant fuzzy is used to describe the hesitant psychology of decision-makers in selecting suppliers, the variance fluctuation is used to describe the characteristics of hesitant fuzzy numbers, and the probability is used to measure the uncertainty of the environment. A green supplier evaluation model under the uncertainty environment is proposed, which comprehensively evaluates the green suppliers under the uncertain environment. Furthermore, it is compared with other methods that do not consider the uncertainty and the adaptability of evaluation method and right confirmation method, so as to reflect the influence of uncertainty to green supplier evaluation and the importance of adaptability of evaluation method and right confirmation method.


2013 ◽  
Vol 470 ◽  
pp. 683-688
Author(s):  
Hai Yang Jiang ◽  
Hua Qing Wang ◽  
Peng Chen

This paper proposes a novel fault diagnosis method for rotating machinery based on symptom parameters and Bayesian Network. Non-dimensional symptom parameters in frequency domain calculated from vibration signals are defined for reflecting the features of vibration signals. In addition, sensitive evaluation method for selecting good non-dimensional symptom parameters using the method of discrimination index is also proposed for detecting and distinguishing faults in rotating machinery. Finally, the application example of diagnosis for a roller bearing by Bayesian Network is given. Diagnosis results show the methods proposed in this paper are effective.


電腦學刊 ◽  
2021 ◽  
Vol 32 (6) ◽  
pp. 239-247
Author(s):  
Fu-Zhong Wu Fu-Zhong Wu ◽  
Qing-Mei Lv Fu-Zhong Wu ◽  
En Fan Qing-Mei Lv


2019 ◽  
Vol 56 (5) ◽  
pp. 051003
Author(s):  
方浩 Fang Hao ◽  
李艾华 Li Aihua ◽  
王涛 Wang Tao ◽  
常红伟 Chang Hongwei

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