Pub Date : 2007-06-01DOI: 10.30016/JGS.200706.0005
D. Yamaguchi, GuoDong Li, Kozo Mizutani Takahiro Akabane, M. Nagai, M. Kitaoka
Grey Structural Modeling (GSM for short) is a new approach of system modeling method succeeding to ISM and FSM. GSM is based on the two procedures: estimating a hierarchy of the elements and estimating paths among the elements. The former is constructed from complex equations including set operation. In this paper, a significant algorithm of the GSM procedure is presented for reliable implementation. The main problem we should solve is how to group the elements into several classes and to determine their hierarchy in the computation. First of all, these procedures are shown in a pseudo language with several figures. The main idea is that two new arrays are defined to manage the elements of hierarchy, and the set operation is founded on the matrix and those arrays computation. Three examples in decision-making are shown with the developed program. The result shows that this algorithm is reliable and the developed program is useful for decision-making.
{"title":"A Realization Algorithm of Grey Structural Modeling","authors":"D. Yamaguchi, GuoDong Li, Kozo Mizutani Takahiro Akabane, M. Nagai, M. Kitaoka","doi":"10.30016/JGS.200706.0005","DOIUrl":"https://doi.org/10.30016/JGS.200706.0005","url":null,"abstract":"Grey Structural Modeling (GSM for short) is a new approach of system modeling method succeeding to ISM and FSM. GSM is based on the two procedures: estimating a hierarchy of the elements and estimating paths among the elements. The former is constructed from complex equations including set operation. In this paper, a significant algorithm of the GSM procedure is presented for reliable implementation. The main problem we should solve is how to group the elements into several classes and to determine their hierarchy in the computation. First of all, these procedures are shown in a pseudo language with several figures. The main idea is that two new arrays are defined to manage the elements of hierarchy, and the set operation is founded on the matrix and those arrays computation. Three examples in decision-making are shown with the developed program. The result shows that this algorithm is reliable and the developed program is useful for decision-making.","PeriodicalId":50187,"journal":{"name":"Journal of Grey System","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2007-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70056288","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2007-06-01DOI: 10.30016/JGS.200706.0001
Li-Chu Hung
We examine the accuracy of the model with empirical study focusing on regression analysis in econometric model. Then we compare the result from the model and that from the four GM (1, 1) shadow models in grey forecast. To appraise the ability of the forecasting model, we use MAPE (Mean Absolute Percentage Error) to examine the accuracy of the model. We find all the MAPE values are between 10~20, which yield an excellent forecasting ability. Though the values forecasted by 4 GM (1, 1) shadow models are larger than those from the forecasting model built by this research, they are within the scope excellent forecasting ability to prove that we can replace econometric regression forecasting model with grey forecast partially.
{"title":"The Study of Grey Forecasting in Replacement for Economic Forecasting Model","authors":"Li-Chu Hung","doi":"10.30016/JGS.200706.0001","DOIUrl":"https://doi.org/10.30016/JGS.200706.0001","url":null,"abstract":"We examine the accuracy of the model with empirical study focusing on regression analysis in econometric model. Then we compare the result from the model and that from the four GM (1, 1) shadow models in grey forecast. To appraise the ability of the forecasting model, we use MAPE (Mean Absolute Percentage Error) to examine the accuracy of the model. We find all the MAPE values are between 10~20, which yield an excellent forecasting ability. Though the values forecasted by 4 GM (1, 1) shadow models are larger than those from the forecasting model built by this research, they are within the scope excellent forecasting ability to prove that we can replace econometric regression forecasting model with grey forecast partially.","PeriodicalId":50187,"journal":{"name":"Journal of Grey System","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2007-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70056096","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2007-06-01DOI: 10.30016/JGS.200706.0007
Meng Lu, K. Wevers
Grey system theory was initiated in the beginning of 1980s. Since then the research on theory development and applications is progressing. However, until today nearly all researchers of grey system theory are from Chinese speaking areas, and the theory is still hardly known nor accepted in the western world. The paper addresses the state-of-the-art development of grey system theory and its application. It aims to highlight and analyse relevant issues (i.e. obstacles, possible solutions and potential trends) for further research from the perspective both of grey system theory and of the grey system methods.
{"title":"Grey System Theory and Applications: A Way Forward","authors":"Meng Lu, K. Wevers","doi":"10.30016/JGS.200706.0007","DOIUrl":"https://doi.org/10.30016/JGS.200706.0007","url":null,"abstract":"Grey system theory was initiated in the beginning of 1980s. Since then the research on theory development and applications is progressing. However, until today nearly all researchers of grey system theory are from Chinese speaking areas, and the theory is still hardly known nor accepted in the western world. The paper addresses the state-of-the-art development of grey system theory and its application. It aims to highlight and analyse relevant issues (i.e. obstacles, possible solutions and potential trends) for further research from the perspective both of grey system theory and of the grey system methods.","PeriodicalId":50187,"journal":{"name":"Journal of Grey System","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2007-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70056330","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2007-06-01DOI: 10.30016/JGS.200706.0004
Shuo-Pei Chen, C. Shih
As market competition intensifies, most companies realize that they have to constantly develop new products to survive the competition. Though there is always a great risk involved with product development. The accurate anticipation of product diffusion will help reduce the risk of blind investment. In this study a comprehensive procedure for analyzing the diffusion of new product launching is proposed. The new procedure is comprised of two stages: (a) first the major factors that influence the diffusion of products most are identified using the grey relational analysis and (b) secondly an improved grey prediction model is then used to predict the product diffusion based on the selected factors. The improved grey prediction model, called the GMC model, uses convolution integration to promote the forecasting ability of the traditional GM model. The diffusion data of several product categories are examined. The results show that different major macroeconomic indices need to be used in the prediction model according to whether the goods are durable or non-durable. The inclusion of these macroeconomic indices in the GMC model can significantly improve the prediction accuracy. The proposed procedure can help companies improve their prediction ability and provide managers with more marketing information.
{"title":"Diffusion Forecasting of Innovative Products Using an Improved Grey Model","authors":"Shuo-Pei Chen, C. Shih","doi":"10.30016/JGS.200706.0004","DOIUrl":"https://doi.org/10.30016/JGS.200706.0004","url":null,"abstract":"As market competition intensifies, most companies realize that they have to constantly develop new products to survive the competition. Though there is always a great risk involved with product development. The accurate anticipation of product diffusion will help reduce the risk of blind investment. In this study a comprehensive procedure for analyzing the diffusion of new product launching is proposed. The new procedure is comprised of two stages: (a) first the major factors that influence the diffusion of products most are identified using the grey relational analysis and (b) secondly an improved grey prediction model is then used to predict the product diffusion based on the selected factors. The improved grey prediction model, called the GMC model, uses convolution integration to promote the forecasting ability of the traditional GM model. The diffusion data of several product categories are examined. The results show that different major macroeconomic indices need to be used in the prediction model according to whether the goods are durable or non-durable. The inclusion of these macroeconomic indices in the GMC model can significantly improve the prediction accuracy. The proposed procedure can help companies improve their prediction ability and provide managers with more marketing information.","PeriodicalId":50187,"journal":{"name":"Journal of Grey System","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2007-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70056149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2006-12-01DOI: 10.30016/JGS.200612.0007
Chang-Jo Wu, Fu-Yuan Hsu, Kun-Li Wen, John H. Wu
In the GM (1,1) study, generally speaking, the original data are non-smoothing type. But, actually, many types of data are smoothing and nonlinear. Such as population model, that is shown the saturation behavior in where. Hence, Deng and Wen proposed Verhulst model in GM (1,1) model to analyze this type of original data. However, the formula has some missing. Therefore, in this paper, we not only present the novel application for GM(1,1|α) to solve the problem, but also suggest the 4-points rolling in GM(1,1|α) is the better method in this field.
{"title":"The Study of GM (1,1|α) on the Verhulst Model","authors":"Chang-Jo Wu, Fu-Yuan Hsu, Kun-Li Wen, John H. Wu","doi":"10.30016/JGS.200612.0007","DOIUrl":"https://doi.org/10.30016/JGS.200612.0007","url":null,"abstract":"In the GM (1,1) study, generally speaking, the original data are non-smoothing type. But, actually, many types of data are smoothing and nonlinear. Such as population model, that is shown the saturation behavior in where. Hence, Deng and Wen proposed Verhulst model in GM (1,1) model to analyze this type of original data. However, the formula has some missing. Therefore, in this paper, we not only present the novel application for GM(1,1|α) to solve the problem, but also suggest the 4-points rolling in GM(1,1|α) is the better method in this field.","PeriodicalId":50187,"journal":{"name":"Journal of Grey System","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2006-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70055840","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2006-12-01DOI: 10.30016/JGS.200612.0005
Sifeng Liu, Zhigeng Fang, Yi Lin
Based on the definition of degree of grey incidence, which put forward by Professor Ju-Long Deng, a new definition of absolute degree of grey incidence is given in this paper. And a simplified method to calculate the new absolute degree of grey incidence is put forward and proved. The properties of the new definition of absolute degree of grey incidence are studied. Compared with the original definition, the new definition has many advantages such as (1) satisfies the properties of symmetry, (2) the order of grey incidences remain stable, and (3) with smaller amount of computation, etc.
{"title":"Study on a New Definition of Degree of Grey Incidence","authors":"Sifeng Liu, Zhigeng Fang, Yi Lin","doi":"10.30016/JGS.200612.0005","DOIUrl":"https://doi.org/10.30016/JGS.200612.0005","url":null,"abstract":"Based on the definition of degree of grey incidence, which put forward by Professor Ju-Long Deng, a new definition of absolute degree of grey incidence is given in this paper. And a simplified method to calculate the new absolute degree of grey incidence is put forward and proved. The properties of the new definition of absolute degree of grey incidence are studied. Compared with the original definition, the new definition has many advantages such as (1) satisfies the properties of symmetry, (2) the order of grey incidences remain stable, and (3) with smaller amount of computation, etc.","PeriodicalId":50187,"journal":{"name":"Journal of Grey System","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2006-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70055637","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2006-12-01DOI: 10.30016/JGS.200612.0009
D. Guo, R. Guo, C. Thiart
The GM (1,1) model is a small-sample based coupled data-assimilation approach with the advantages of highly predictive power and easy computations. However, in the standard GM (1,1) model building exercises we often face a statistical-grey inconsistency problem. Therefore, in this paper we examine the GM(1,1) model from its component-level and try to reveal an interactive coupling nature of differential equation model and corresponding regression model constituting of a GM(1,1) model. Based our analysis, we state a coupling principle for establishing an extended GM(1,1) model and further explore certain families of extended GM(1,1) models with statistical-grey consistency.
{"title":"The Coupling of Regression Model and Differential Equation Model in GM (1, 1) Modeling and Extended GM (1, 1) Models","authors":"D. Guo, R. Guo, C. Thiart","doi":"10.30016/JGS.200612.0009","DOIUrl":"https://doi.org/10.30016/JGS.200612.0009","url":null,"abstract":"The GM (1,1) model is a small-sample based coupled data-assimilation approach with the advantages of highly predictive power and easy computations. However, in the standard GM (1,1) model building exercises we often face a statistical-grey inconsistency problem. Therefore, in this paper we examine the GM(1,1) model from its component-level and try to reveal an interactive coupling nature of differential equation model and corresponding regression model constituting of a GM(1,1) model. Based our analysis, we state a coupling principle for establishing an extended GM(1,1) model and further explore certain families of extended GM(1,1) models with statistical-grey consistency.","PeriodicalId":50187,"journal":{"name":"Journal of Grey System","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2006-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70056087","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2006-12-01DOI: 10.30016/JGS.200612.0002
Yung-Fa Huang, Ching-Mu Chen, Lih-Ren Hwang
In this paper, we propose an adaptive grey predictor (AGP) that aims at the short-term fading (STF) of noisy Rayleigh channels in the mobile communication systems. Here, we use a moving window to reduce the degradation by the additive white Gaussian noise and further improve the precision of the STF prediction of the adaptive segmental grey prediction model, GM (1, 1, α, β). Computer simulation results show that choosing an appropriate length of moving windows in the proposed window AGP (WAGP) can obtain better accuracy and large performance improvement on the noisy STF prediction.
{"title":"Performance of a Novel Adaptive Grey Predictor for Rayleigh Fading Channels in Mobile Communications","authors":"Yung-Fa Huang, Ching-Mu Chen, Lih-Ren Hwang","doi":"10.30016/JGS.200612.0002","DOIUrl":"https://doi.org/10.30016/JGS.200612.0002","url":null,"abstract":"In this paper, we propose an adaptive grey predictor (AGP) that aims at the short-term fading (STF) of noisy Rayleigh channels in the mobile communication systems. Here, we use a moving window to reduce the degradation by the additive white Gaussian noise and further improve the precision of the STF prediction of the adaptive segmental grey prediction model, GM (1, 1, α, β). Computer simulation results show that choosing an appropriate length of moving windows in the proposed window AGP (WAGP) can obtain better accuracy and large performance improvement on the noisy STF prediction.","PeriodicalId":50187,"journal":{"name":"Journal of Grey System","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2006-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70055327","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2006-12-01DOI: 10.30016/JGS.200612.0003
Shu-Chen Chang
This paper investigates the impacts between exchange-rate uncertainty and unemployment rate during pre- and post-crisis periods and examines the relationship within Asian region, including South Korea, Singapore, Hong Kong and Taiwan. According to the results, GRA has a higher relation than the linear regression with restrictive lag structures model does. The relationship between exchange-rate uncertainty and unemployment rate are high mutually dependent during the pre-crisis period in Taiwan, and South Korea. On the contrary, the relation in Taiwan becomes less dependent during the post-crisis period. The exchange-rate uncertainty has a significant impact on the unemployment rate in Taiwan and South Korea during the pre-crisis period. However, the exchange-rate uncertainty has a significant impact on the unemployment in South Korea during the post-crisis period but it has insignificant impacts on that in others countries during the post-crisis period. Furthermore, the exchange-rate uncertainty is mutually dependent between Taiwan and South Korea during the pre- and post-crisis.
{"title":"Effect of Exchange-Rate Uncertainty on Labor Market Based on the Grey Relational Analysis","authors":"Shu-Chen Chang","doi":"10.30016/JGS.200612.0003","DOIUrl":"https://doi.org/10.30016/JGS.200612.0003","url":null,"abstract":"This paper investigates the impacts between exchange-rate uncertainty and unemployment rate during pre- and post-crisis periods and examines the relationship within Asian region, including South Korea, Singapore, Hong Kong and Taiwan. According to the results, GRA has a higher relation than the linear regression with restrictive lag structures model does. The relationship between exchange-rate uncertainty and unemployment rate are high mutually dependent during the pre-crisis period in Taiwan, and South Korea. On the contrary, the relation in Taiwan becomes less dependent during the post-crisis period. The exchange-rate uncertainty has a significant impact on the unemployment rate in Taiwan and South Korea during the pre-crisis period. However, the exchange-rate uncertainty has a significant impact on the unemployment in South Korea during the post-crisis period but it has insignificant impacts on that in others countries during the post-crisis period. Furthermore, the exchange-rate uncertainty is mutually dependent between Taiwan and South Korea during the pre- and post-crisis.","PeriodicalId":50187,"journal":{"name":"Journal of Grey System","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2006-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70055397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2006-12-01DOI: 10.30016/JGS.200612.0008
Ping Zhou, Yong Wei
Based the principle and characteristic of model GM (1,1), we derive the new formula of background value. And then it could improve the simulation and prediction precision effectively.
根据GM(1,1)模型的原理和特点，推导出新的背景值公式。从而有效地提高了仿真和预测精度。
{"title":"The Optimization of Background Value in Grey Model GM (1,1)","authors":"Ping Zhou, Yong Wei","doi":"10.30016/JGS.200612.0008","DOIUrl":"https://doi.org/10.30016/JGS.200612.0008","url":null,"abstract":"Based the principle and characteristic of model GM (1,1), we derive the new formula of background value. And then it could improve the simulation and prediction precision effectively.","PeriodicalId":50187,"journal":{"name":"Journal of Grey System","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2006-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70056040","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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