Pub Date : 2017-08-01DOI: 10.1109/GSIS.2017.8077721
Xiaoyu Yang, Zhigeng Fang, Liangyan Tao
The reliability evaluation of equipment system with high reliability and long life is widely studied in recent years. It is very hard or uneconomic to obtain enough failure samples of these equipment in reliability test. Although there are empirical information available, we cannot ignore the inaccurate or uncertainty of these information. In this context, a quantitative analysis model of reliability evaluation for equipment system is put forward in view of the few failure data of equipment life test. The multiple working states of the equipment system and random process of equipment state transition are presented by GERT network. Interval grey number is introduced to describe the uncertainty of the statistical data and experience information of GERT parameters. According to GERT matrix solving algorithm, the system equivalent transfer function can be obtained, and then the reliability evaluation of equipment system can be realized. Besides, the study provides a new thinking for reliability accelerated life test.
{"title":"Lifetime evaluation grey GERT network model of equipment system","authors":"Xiaoyu Yang, Zhigeng Fang, Liangyan Tao","doi":"10.1109/GSIS.2017.8077721","DOIUrl":"https://doi.org/10.1109/GSIS.2017.8077721","url":null,"abstract":"The reliability evaluation of equipment system with high reliability and long life is widely studied in recent years. It is very hard or uneconomic to obtain enough failure samples of these equipment in reliability test. Although there are empirical information available, we cannot ignore the inaccurate or uncertainty of these information. In this context, a quantitative analysis model of reliability evaluation for equipment system is put forward in view of the few failure data of equipment life test. The multiple working states of the equipment system and random process of equipment state transition are presented by GERT network. Interval grey number is introduced to describe the uncertainty of the statistical data and experience information of GERT parameters. According to GERT matrix solving algorithm, the system equivalent transfer function can be obtained, and then the reliability evaluation of equipment system can be realized. Besides, the study provides a new thinking for reliability accelerated life test.","PeriodicalId":425920,"journal":{"name":"2017 International Conference on Grey Systems and Intelligent Services (GSIS)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129090615","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-08-01DOI: 10.1109/GSIS.2017.8077712
H. Zhan, Sifeng Liu
As a measuring tool of evaluating teaching performance of Universities, the Excellent courses attract more and more attention. But in practice, how to objectively evaluate excellent courses is still unresolved. This paper tries to evaluate an excellent course of Huangshan University, selling course, based on the grey clustering model. We empirically justified the effectiveness of this method and followed with suggestions on local Universities' evaluation of excellent courses.
{"title":"Application of grey clustering evaluation model to construction of university excellent courses","authors":"H. Zhan, Sifeng Liu","doi":"10.1109/GSIS.2017.8077712","DOIUrl":"https://doi.org/10.1109/GSIS.2017.8077712","url":null,"abstract":"As a measuring tool of evaluating teaching performance of Universities, the Excellent courses attract more and more attention. But in practice, how to objectively evaluate excellent courses is still unresolved. This paper tries to evaluate an excellent course of Huangshan University, selling course, based on the grey clustering model. We empirically justified the effectiveness of this method and followed with suggestions on local Universities' evaluation of excellent courses.","PeriodicalId":425920,"journal":{"name":"2017 International Conference on Grey Systems and Intelligent Services (GSIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115601498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-08-01DOI: 10.1109/GSIS.2017.8077698
Tianxiang Yao, Hong Gao
The purpose of establishing buffer operators is to improve the smooth degree, then increase the simulation accuracy of the model. This paper probed into modeling mechanism of several typical buffer operators such as the arithmetic buffer operators, the buffer operators with monotonic function and weighted buffer operators. The results indicates that after infinite buffer operators, no matter we adopt a weakening buffer operator or a strengthen buffer operator, the raw sequence can be changed into a constant sequence. Because discrete GM(1,1) model can completely simulate constant sequence, the simulation accuracy is 100%. Because discrete GM(1,1) model is the accurate form of GM(1,1) model, after infinite buffer operator, GM(1,1) model can have very high simulation accuracy.
{"title":"Properties of buffer operators based on discrete GM(1,1) model","authors":"Tianxiang Yao, Hong Gao","doi":"10.1109/GSIS.2017.8077698","DOIUrl":"https://doi.org/10.1109/GSIS.2017.8077698","url":null,"abstract":"The purpose of establishing buffer operators is to improve the smooth degree, then increase the simulation accuracy of the model. This paper probed into modeling mechanism of several typical buffer operators such as the arithmetic buffer operators, the buffer operators with monotonic function and weighted buffer operators. The results indicates that after infinite buffer operators, no matter we adopt a weakening buffer operator or a strengthen buffer operator, the raw sequence can be changed into a constant sequence. Because discrete GM(1,1) model can completely simulate constant sequence, the simulation accuracy is 100%. Because discrete GM(1,1) model is the accurate form of GM(1,1) model, after infinite buffer operator, GM(1,1) model can have very high simulation accuracy.","PeriodicalId":425920,"journal":{"name":"2017 International Conference on Grey Systems and Intelligent Services (GSIS)","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116161212","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Complex systems and their components usually have various performance states and the reliability parameters are normally uncertain. Modeling theories that are developed on the basis of binary outcomes and precise reliability information lack sufficient abilities to describe the above phenomena. In this paper, grey system theory and Bayesian network are employed to analyze the reliability of complex system. First, interval grey number is applied to represent the performance state as well as the conditional probability, which can avoid the loss of important reliability information. Second, the intervals of reliability characteristic parameters such as fault rate and posterior probability are obtained with Bayesian network inference and grey global optimization algorithm. Afterwards, vulnerable components and probabilities of possible states can be identified by using comparison rules of interval grey numbers, which is conducive to reliability analysis and fault diagnosis of complex system. Finally, a case about civil aircraft hydraulic system is studied, showing that the proposed approach is effective and convenient for reliability modelling and analysis of multi-state and uncertain systems.
{"title":"Grey Bayesian network model for reliability analysis of complex system","authors":"Yingsai Cao, Sifeng Liu, Zhigeng Fang, Wen-jie Dong","doi":"10.1109/GSIS.2017.8077720","DOIUrl":"https://doi.org/10.1109/GSIS.2017.8077720","url":null,"abstract":"Complex systems and their components usually have various performance states and the reliability parameters are normally uncertain. Modeling theories that are developed on the basis of binary outcomes and precise reliability information lack sufficient abilities to describe the above phenomena. In this paper, grey system theory and Bayesian network are employed to analyze the reliability of complex system. First, interval grey number is applied to represent the performance state as well as the conditional probability, which can avoid the loss of important reliability information. Second, the intervals of reliability characteristic parameters such as fault rate and posterior probability are obtained with Bayesian network inference and grey global optimization algorithm. Afterwards, vulnerable components and probabilities of possible states can be identified by using comparison rules of interval grey numbers, which is conducive to reliability analysis and fault diagnosis of complex system. Finally, a case about civil aircraft hydraulic system is studied, showing that the proposed approach is effective and convenient for reliability modelling and analysis of multi-state and uncertain systems.","PeriodicalId":425920,"journal":{"name":"2017 International Conference on Grey Systems and Intelligent Services (GSIS)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121422007","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-08-01DOI: 10.1109/GSIS.2017.8077673
Miao Ma, Bolong Wang
Aiming at the performance evaluation on image captioning and video captioning, this paper discusses the existing performance metrics and then suggests a novel overall performance metric based on grey relational analysis of Grey System Theory. In our metric, all the available performance metrics of each captioning model is used to extract a comparative sequence. Meanwhile, a reference sequence is constructed by combining all the available performance metrics involved. Then an overall metric is obtained by computing the grey relational degrees between the two kinds of sequences. Experimental results on the most widely-used image dataset and video dataset show that the proposed metric is fast and effective that helps for spurring improvements and measuring progress in the state of the art of image captioning and video captioning.
{"title":"A grey relational analysis based evaluation metric for image captioning and video captioning","authors":"Miao Ma, Bolong Wang","doi":"10.1109/GSIS.2017.8077673","DOIUrl":"https://doi.org/10.1109/GSIS.2017.8077673","url":null,"abstract":"Aiming at the performance evaluation on image captioning and video captioning, this paper discusses the existing performance metrics and then suggests a novel overall performance metric based on grey relational analysis of Grey System Theory. In our metric, all the available performance metrics of each captioning model is used to extract a comparative sequence. Meanwhile, a reference sequence is constructed by combining all the available performance metrics involved. Then an overall metric is obtained by computing the grey relational degrees between the two kinds of sequences. Experimental results on the most widely-used image dataset and video dataset show that the proposed metric is fast and effective that helps for spurring improvements and measuring progress in the state of the art of image captioning and video captioning.","PeriodicalId":425920,"journal":{"name":"2017 International Conference on Grey Systems and Intelligent Services (GSIS)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121474765","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-08-01DOI: 10.1109/GSIS.2017.8077724
Changwen Zhang
This paper investigates characterizations of semiinfinite convex programming, and obtains conditions of optimal solutions of semi-infinite convex programming by using saddle point criteria.
研究了半无限凸规划的一些性质，利用鞍点准则得到了半无限凸规划最优解的条件。
{"title":"Sufficient and necessary conditions of optimal solutions of semi-infinite convex programing","authors":"Changwen Zhang","doi":"10.1109/GSIS.2017.8077724","DOIUrl":"https://doi.org/10.1109/GSIS.2017.8077724","url":null,"abstract":"This paper investigates characterizations of semiinfinite convex programming, and obtains conditions of optimal solutions of semi-infinite convex programming by using saddle point criteria.","PeriodicalId":425920,"journal":{"name":"2017 International Conference on Grey Systems and Intelligent Services (GSIS)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122608552","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-08-01DOI: 10.1109/GSIS.2017.8077692
Qing Li
The aims of this study were to forecast change of Chinese social donation in recent years by grey Verhulst model to find out characteristics of social donation and grey correlation analysis which was proposed by Professor Deng Julong is used to detect of an interpersonal relationship between the number of social donations from oversea and the number of foundations. This paper provides a quantitative method to study the trend of Chinese social donation. Grey system theory has been used into economy, administration, society and other fields. The reason is that grey system theory can deal with partially unknown parameters in a system and predict behavior of unknown system within a small data. So grey system theory is superiority to other ways. In order to improve precise, grey system theory is introduced into social donation to explain the phenomenon of social donation. Grey system theory consists of grey Verhulst model and grey relative degree. There is a distinct difference between grey Verhulst model and linear equation because of grey Verhulst model can greatly eliminate the stimulation error in small data. Therefore the reliability of predictive model for social donation is examined by Grey Verhulst model and a relationship of both variables for soical donation and foundation is demonstrated by grey relative degree in the small data. According to the original data of Chinese social donation from China Civil Affairs' Statistical Yearbook as well as China Civil Affairs' website between 2012 and 2016, the original data of social donation has meet basic condition of prediction because the data with S-shaped curve indicates growth saturation by simulation. Based on law of data fitting, model of social donation is built and make calculation by formula of grey Verhulst model. This way needn't take a leap from difference equation to differential equation and this model is tested by mean relative error, predictive value along with relative error by inverse accumulated generating operation. Briefly speaking, the patterns of social donation will be identified by the following steps to achieve high forecast accuracy in small data. Original sequences are (572.50, 566.40, 604.40, 654.50, 827.00). The new sequences are generated by 1-IAGO (Inverse Accumulated Generating Operation) from the original data sequences for (572.5000, −6.1000, 38.0000, 50.1000, 172.5000). Mean generation with consecutive neighbors is (569.4500, 585.4000, 629.4500, 740.7500). Grey differential equation for LSE (Least-Square Estimation) of parameters vector is a=0.7189 and b=0.0013.
{"title":"Application grey system theory on prediction of Chinese social donation","authors":"Qing Li","doi":"10.1109/GSIS.2017.8077692","DOIUrl":"https://doi.org/10.1109/GSIS.2017.8077692","url":null,"abstract":"The aims of this study were to forecast change of Chinese social donation in recent years by grey Verhulst model to find out characteristics of social donation and grey correlation analysis which was proposed by Professor Deng Julong is used to detect of an interpersonal relationship between the number of social donations from oversea and the number of foundations. This paper provides a quantitative method to study the trend of Chinese social donation. Grey system theory has been used into economy, administration, society and other fields. The reason is that grey system theory can deal with partially unknown parameters in a system and predict behavior of unknown system within a small data. So grey system theory is superiority to other ways. In order to improve precise, grey system theory is introduced into social donation to explain the phenomenon of social donation. Grey system theory consists of grey Verhulst model and grey relative degree. There is a distinct difference between grey Verhulst model and linear equation because of grey Verhulst model can greatly eliminate the stimulation error in small data. Therefore the reliability of predictive model for social donation is examined by Grey Verhulst model and a relationship of both variables for soical donation and foundation is demonstrated by grey relative degree in the small data. According to the original data of Chinese social donation from China Civil Affairs' Statistical Yearbook as well as China Civil Affairs' website between 2012 and 2016, the original data of social donation has meet basic condition of prediction because the data with S-shaped curve indicates growth saturation by simulation. Based on law of data fitting, model of social donation is built and make calculation by formula of grey Verhulst model. This way needn't take a leap from difference equation to differential equation and this model is tested by mean relative error, predictive value along with relative error by inverse accumulated generating operation. Briefly speaking, the patterns of social donation will be identified by the following steps to achieve high forecast accuracy in small data. Original sequences are (572.50, 566.40, 604.40, 654.50, 827.00). The new sequences are generated by 1-IAGO (Inverse Accumulated Generating Operation) from the original data sequences for (572.5000, −6.1000, 38.0000, 50.1000, 172.5000). Mean generation with consecutive neighbors is (569.4500, 585.4000, 629.4500, 740.7500). Grey differential equation for LSE (Least-Square Estimation) of parameters vector is a=0.7189 and b=0.0013.","PeriodicalId":425920,"journal":{"name":"2017 International Conference on Grey Systems and Intelligent Services (GSIS)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116024618","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-08-01DOI: 10.1109/GSIS.2017.8077711
Yuhong Wang, Wenchao Zuo, Yong Liu
Existing clustering algorithms need to specify the number of clusters and to select initial points using human input, which lead to inferior clustering and optimisation outputs. Here, an improved grey decision-making model based on the thought of affinity propagation algorithm and grey correlation analysis is proposed to solve these problems. According to the panel data class and the inter-class candidate points between the message dissemination for clustering, we fully mine all information contained in a multi-indicator panel dataset. Finally, a case study is used to test the improved model's validity and rationality.
{"title":"Study on the improved grey decision-making model and its application","authors":"Yuhong Wang, Wenchao Zuo, Yong Liu","doi":"10.1109/GSIS.2017.8077711","DOIUrl":"https://doi.org/10.1109/GSIS.2017.8077711","url":null,"abstract":"Existing clustering algorithms need to specify the number of clusters and to select initial points using human input, which lead to inferior clustering and optimisation outputs. Here, an improved grey decision-making model based on the thought of affinity propagation algorithm and grey correlation analysis is proposed to solve these problems. According to the panel data class and the inter-class candidate points between the message dissemination for clustering, we fully mine all information contained in a multi-indicator panel dataset. Finally, a case study is used to test the improved model's validity and rationality.","PeriodicalId":425920,"journal":{"name":"2017 International Conference on Grey Systems and Intelligent Services (GSIS)","volume":"122 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131807523","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Considering the different types of equipment manufacturing industries, consumers' differentiated preferences for Chinese domestic equipment manufacturers and multinational equipment manufacturers, as well as the uncertainty of technological level and dependence on production factor in reality, this paper introduces the interval grey number into the Stackelberg game model, and analyzes the market share of two competing enterprises and the consumer preferences for both of their products based on different industrial types. The results show that when both of the competing firms are engaged in R&D activities, consumers prefer domestic products, and with the improvement of technological level, this preference grows stronger, but the market share of the multinational enterprise is higher than that of local enterprises. When the two competing enterprises are engaged in manufacturing activities, consumers are more inclined to choose products of the multinational company, and with the increasing dependence on production factors, the preference becomes stronger. Meanwhile the market share of the multinational company is higher than the local enterprise. Therefore, from the perspective of consumer preference, China's domestic equipment manufacturing enterprises should choose technology-intensive or technology & labor-intensive industries (or dual-intensive industries).
{"title":"Grey game research about customer preference, international competition and the choice of industrial type","authors":"Yuhang Zhang, Y. Wang, Qixin Liu","doi":"10.1108/GS-10-2017-0033","DOIUrl":"https://doi.org/10.1108/GS-10-2017-0033","url":null,"abstract":"Considering the different types of equipment manufacturing industries, consumers' differentiated preferences for Chinese domestic equipment manufacturers and multinational equipment manufacturers, as well as the uncertainty of technological level and dependence on production factor in reality, this paper introduces the interval grey number into the Stackelberg game model, and analyzes the market share of two competing enterprises and the consumer preferences for both of their products based on different industrial types. The results show that when both of the competing firms are engaged in R&D activities, consumers prefer domestic products, and with the improvement of technological level, this preference grows stronger, but the market share of the multinational enterprise is higher than that of local enterprises. When the two competing enterprises are engaged in manufacturing activities, consumers are more inclined to choose products of the multinational company, and with the increasing dependence on production factors, the preference becomes stronger. Meanwhile the market share of the multinational company is higher than the local enterprise. Therefore, from the perspective of consumer preference, China's domestic equipment manufacturing enterprises should choose technology-intensive or technology & labor-intensive industries (or dual-intensive industries).","PeriodicalId":425920,"journal":{"name":"2017 International Conference on Grey Systems and Intelligent Services (GSIS)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116642574","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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