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":"9 1","pages":"143-153"},"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":"9 1","pages":"87-92"},"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":"9 1","pages":"93-101"},"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":"9 1","pages":"139-142"},"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}
Pub Date : 2006-06-01DOI: 10.30016/JGS.200606.0009
Fu-Yuan Hsu, Chang-Jo Wu, Kun-Li Wen, John H. Wu
In the GM (1,1) study, the essential problem is ”how to establish the new known model to simulation the unknown given system, and to determine the best prediction results for the given system, in the other saying, the least error between real system to simulation model”. In this study, the graphical polygon area analyses are used to estimate the error of the number of equations in Least Square Method (LSQ Method) procedure and the value for the mean square error (MSE) analyses to determine a adjustable value of α in GM(1,1|α ). There are eight kinds of different data for original system’s output to analyze.
{"title":"The Pure Numerical Graphical Study on The Errors of GM (1,1|α)","authors":"Fu-Yuan Hsu, Chang-Jo Wu, Kun-Li Wen, John H. Wu","doi":"10.30016/JGS.200606.0009","DOIUrl":"https://doi.org/10.30016/JGS.200606.0009","url":null,"abstract":"In the GM (1,1) study, the essential problem is ”how to establish the new known model to simulation the unknown given system, and to determine the best prediction results for the given system, in the other saying, the least error between real system to simulation model”. In this study, the graphical polygon area analyses are used to estimate the error of the number of equations in Least Square Method (LSQ Method) procedure and the value for the mean square error (MSE) analyses to determine a adjustable value of α in GM(1,1|α ). There are eight kinds of different data for original system’s output to analyze.","PeriodicalId":50187,"journal":{"name":"Journal of Grey System","volume":"9 1","pages":"65-74"},"PeriodicalIF":1.6,"publicationDate":"2006-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70055290","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 : 2006-06-01DOI: 10.30016/JGS.200606.0003
Yo-Ping Huang, Tsun-Wei Chang
With the explosive growth of multimedia applications, the quality and ability to retrieve images in an efficient way is a challenge to researchers. A new shape-based image retrieval model is presented to improve the recall rate of image retrieval system. The retrieval procedures consist of two major steps: the feature representation of object's shape and the image retrieval method. The shape signatures are extracted along the object boundary to form a data sequence for grey model. After deriving the feature sequences, both grey relational analysis and GM(1,N) model are integrated to construct the proposed image retrieval model. A fish data set is selected to test the reconstructed error rates when different comparative images are chosen for the GM(1,N) model. Experimental results from the fish shape library verify the effectiveness of the proposed model.
{"title":"Designing a Shape-Based Image Retrieval System by Grey Relational Analysis and GM(1,N) Model","authors":"Yo-Ping Huang, Tsun-Wei Chang","doi":"10.30016/JGS.200606.0003","DOIUrl":"https://doi.org/10.30016/JGS.200606.0003","url":null,"abstract":"With the explosive growth of multimedia applications, the quality and ability to retrieve images in an efficient way is a challenge to researchers. A new shape-based image retrieval model is presented to improve the recall rate of image retrieval system. The retrieval procedures consist of two major steps: the feature representation of object's shape and the image retrieval method. The shape signatures are extracted along the object boundary to form a data sequence for grey model. After deriving the feature sequences, both grey relational analysis and GM(1,N) model are integrated to construct the proposed image retrieval model. A fish data set is selected to test the reconstructed error rates when different comparative images are chosen for the GM(1,N) model. Experimental results from the fish shape library verify the effectiveness of the proposed model.","PeriodicalId":50187,"journal":{"name":"Journal of Grey System","volume":"9 1","pages":"15-22"},"PeriodicalIF":1.6,"publicationDate":"2006-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70062279","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 : 2006-06-01DOI: 10.30016/JGS.200606.0005
Pi-Fang Hsu, Mei-Ghing Hsu
Based on the Statistical Information Service of the Department of Health of the Executive Yuan of Taiwan, this study describes human resource statistical data of healthcare professionals using the GM (1,1) Model of Grey Theory. Analytical results indicated that using this GM (1,1) Model of the Grey Theory for forecasting achieves an accuracy exceeding 92.36%. Furthermore, Taiwanese healthcare professionals find it extremely difficult to constantly estimate the direction of constantly changing domestic health policies. Empirical results indicated that, from 2000 to 2004, the number of licensed medical personnel in Taiwan declined by 2.06%. Given the excessive demands of nurses and physicians, considerable adjustment is necessary in the future with respect to the quality and quantity of these professionals. Results of this study provide a valuable reference for governmental authorities such as the Department of Health in devising and implementing personnel policies.
{"title":"Accurately Forecasting Supply of and Demand for Taiwanese Healthcare Professionals Using the Grey Theory","authors":"Pi-Fang Hsu, Mei-Ghing Hsu","doi":"10.30016/JGS.200606.0005","DOIUrl":"https://doi.org/10.30016/JGS.200606.0005","url":null,"abstract":"Based on the Statistical Information Service of the Department of Health of the Executive Yuan of Taiwan, this study describes human resource statistical data of healthcare professionals using the GM (1,1) Model of Grey Theory. Analytical results indicated that using this GM (1,1) Model of the Grey Theory for forecasting achieves an accuracy exceeding 92.36%. Furthermore, Taiwanese healthcare professionals find it extremely difficult to constantly estimate the direction of constantly changing domestic health policies. Empirical results indicated that, from 2000 to 2004, the number of licensed medical personnel in Taiwan declined by 2.06%. Given the excessive demands of nurses and physicians, considerable adjustment is necessary in the future with respect to the quality and quantity of these professionals. Results of this study provide a valuable reference for governmental authorities such as the Department of Health in devising and implementing personnel policies.","PeriodicalId":50187,"journal":{"name":"Journal of Grey System","volume":"9 1","pages":"35-41"},"PeriodicalIF":1.6,"publicationDate":"2006-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70062364","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 : 2006-06-01DOI: 10.30016/JGS.200606.0007
Neng-Yih Shih, Neng-Jin Shih, Wen-Chun Yu
In this paper, we proposes a Time-Varying GM (1,1) (TVGM(1,1)), and using recursive least square with forgetting factor to estimate model parameters. The TVGM (1,1) provide adaptation parameter for the data does not unity environment. Which we can track system response well. From computer simulation indeed show the excellent performance, and what's more, the smoothing method and background value method for preprocessing data in the traditional GM(1,1) can be also applied to the proposed TVGM (1,1) to increase the system reliability and extend the application fields.
{"title":"The Parameter Estimation of Time-varying GM(1,1)","authors":"Neng-Yih Shih, Neng-Jin Shih, Wen-Chun Yu","doi":"10.30016/JGS.200606.0007","DOIUrl":"https://doi.org/10.30016/JGS.200606.0007","url":null,"abstract":"In this paper, we proposes a Time-Varying GM (1,1) (TVGM(1,1)), and using recursive least square with forgetting factor to estimate model parameters. The TVGM (1,1) provide adaptation parameter for the data does not unity environment. Which we can track system response well. From computer simulation indeed show the excellent performance, and what's more, the smoothing method and background value method for preprocessing data in the traditional GM(1,1) can be also applied to the proposed TVGM (1,1) to increase the system reliability and extend the application fields.","PeriodicalId":50187,"journal":{"name":"Journal of Grey System","volume":"9 1","pages":"51-56"},"PeriodicalIF":1.6,"publicationDate":"2006-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70055086","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 : 2006-06-01DOI: 10.30016/JGS.200606.0004
D. Yamaguchi, GuoDong Li, K. Mizutani, T. Akabane, M. Nagai, M. Kitaoka
In this paper we developed new grey relational analysis by expanding a range of treatable value. The classical GRA procedure deals with almost whitened values, reference vectors (or sequences), inspected vectors and grey relational grades. The classical GRA is called White-In-White-Out (WIWO) GRA in this paper. We developed two kinds of GRA algorithm based on the topological-based GRA, after defined several new operations of the interval grey number. On the one hand, GRA which provides the grey relational grade a whitened value finally is named Grey-In-White-Out (GIWO) GRA. On the other hand, GRA which provides the grey relational grade the interval grey number is named Grey-In-Grey-Out (GIGO) GRA. Both new GRA procedures deal with the reference vector and inspected vectors as the interval grey number. Three examples are given in this paper; the properties of the grey relational grade given by the proposals are discussed.
{"title":"On the Generalization of Grey Relational Analysis","authors":"D. Yamaguchi, GuoDong Li, K. Mizutani, T. Akabane, M. Nagai, M. Kitaoka","doi":"10.30016/JGS.200606.0004","DOIUrl":"https://doi.org/10.30016/JGS.200606.0004","url":null,"abstract":"In this paper we developed new grey relational analysis by expanding a range of treatable value. The classical GRA procedure deals with almost whitened values, reference vectors (or sequences), inspected vectors and grey relational grades. The classical GRA is called White-In-White-Out (WIWO) GRA in this paper. We developed two kinds of GRA algorithm based on the topological-based GRA, after defined several new operations of the interval grey number. On the one hand, GRA which provides the grey relational grade a whitened value finally is named Grey-In-White-Out (GIWO) GRA. On the other hand, GRA which provides the grey relational grade the interval grey number is named Grey-In-Grey-Out (GIGO) GRA. Both new GRA procedures deal with the reference vector and inspected vectors as the interval grey number. Three examples are given in this paper; the properties of the grey relational grade given by the proposals are discussed.","PeriodicalId":50187,"journal":{"name":"Journal of Grey System","volume":"9 1","pages":"23-33"},"PeriodicalIF":1.6,"publicationDate":"2006-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70062321","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 : 2006-06-01DOI: 10.30016/JGS.200606.0008
Mei-Li You, Chien-Wen Wang, Cheng-Kai Yeh
The software in engineering field, even in others filed become most important and more necessary in the 21(superscript st) century, although there are many toolbox, such as fuzzy, chaos,…etc., had been developed in the past, the grey toolbox still seldom and not quite completed. Therefore, in this paper, the focus is on the toolbox of grey generating, ordinal grey relational grade and cardinal grey relational grade by using Matlab, to development the completed grey relational analysis toolbox. Firstly, we preview the whole mathematical foundation of grey relational analysis in detail. Secondly, the mathematics model of grey generating (four difference types), ten kinds of grey relational grade, and two types of grey relational grades (ordinal and cardinal) are presented. Thirdly, based on the mathematics model, we use Matlab to develop the grey relational analysis toolbox. As the results, in this paper, the completed grey relational analysis toolbox, we can say this kind of completed research is the main contribution and is the first research in grey relational analysis. Also can extends in the economy in benefit, for our research, the market price of the completed grey relational analysis toolbox with our evaluation; at least will over US 1,000 dollars. We hope this completed grey relational analysis toolbox is not only to enhance the depth research of grey relation grade, buy also become a new approach for the applications in grey system theory.
{"title":"The Development of Completed Grey Relational Analysis Toolbox via Matlab","authors":"Mei-Li You, Chien-Wen Wang, Cheng-Kai Yeh","doi":"10.30016/JGS.200606.0008","DOIUrl":"https://doi.org/10.30016/JGS.200606.0008","url":null,"abstract":"The software in engineering field, even in others filed become most important and more necessary in the 21(superscript st) century, although there are many toolbox, such as fuzzy, chaos,…etc., had been developed in the past, the grey toolbox still seldom and not quite completed. Therefore, in this paper, the focus is on the toolbox of grey generating, ordinal grey relational grade and cardinal grey relational grade by using Matlab, to development the completed grey relational analysis toolbox. Firstly, we preview the whole mathematical foundation of grey relational analysis in detail. Secondly, the mathematics model of grey generating (four difference types), ten kinds of grey relational grade, and two types of grey relational grades (ordinal and cardinal) are presented. Thirdly, based on the mathematics model, we use Matlab to develop the grey relational analysis toolbox. As the results, in this paper, the completed grey relational analysis toolbox, we can say this kind of completed research is the main contribution and is the first research in grey relational analysis. Also can extends in the economy in benefit, for our research, the market price of the completed grey relational analysis toolbox with our evaluation; at least will over US 1,000 dollars. We hope this completed grey relational analysis toolbox is not only to enhance the depth research of grey relation grade, buy also become a new approach for the applications in grey system theory.","PeriodicalId":50187,"journal":{"name":"Journal of Grey System","volume":"9 1","pages":"57-64"},"PeriodicalIF":1.6,"publicationDate":"2006-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70055275","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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