Pub Date : 2007-11-01DOI: 10.1109/GSIS.2007.4443496
Yang Wenyi, Luo Jian, Yang Junbin, Pang Jianhua, W. Xiaoqiang
A capacity requirement planning is an important feedback link of MRPII/ERP, used to measure the feasibility of the main production planning and material requirements planning. Either RCCP or CRP, the key task is defining production techniques route and man-hour ration. This paper designs the related data structure of capacity requirements planning, and respectively discusses resources list and dividing time period resources list used in the RCCP and CRP program. The system is carried out according to the method and the effect is satisfactory.
{"title":"A study of the method of capacity requirements planning","authors":"Yang Wenyi, Luo Jian, Yang Junbin, Pang Jianhua, W. Xiaoqiang","doi":"10.1109/GSIS.2007.4443496","DOIUrl":"https://doi.org/10.1109/GSIS.2007.4443496","url":null,"abstract":"A capacity requirement planning is an important feedback link of MRPII/ERP, used to measure the feasibility of the main production planning and material requirements planning. Either RCCP or CRP, the key task is defining production techniques route and man-hour ration. This paper designs the related data structure of capacity requirements planning, and respectively discusses resources list and dividing time period resources list used in the RCCP and CRP program. The system is carried out according to the method and the effect is satisfactory.","PeriodicalId":445155,"journal":{"name":"2007 IEEE International Conference on Grey Systems and Intelligent Services","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134525572","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 : 2007-11-01DOI: 10.1109/GSIS.2007.4443431
D. Akay, O. Kulak
Evaluation of product design concepts is an important and critical problem, considering incomplete and imprecise information in the early stages of product design process. In order to solve this problem, grey theory, fuzzy sets and information axiom are combined in this study under the name of grey-fuzzy information axiom for solving product concept evaluation problem for the first time. The information axiom has the capability to solve multi-attribute evaluation problems. Grey and fuzzy set theories are complementary methods for quantification uncertainty. Applicability of the proposed method is demonstrated on the evaluation of dishwasher design concepts. It has been shown that grey-fuzzy information axiom is an appropriate tool to be used for the concept evaluation problem in case of having different types of uncertainties.
{"title":"Evaluation of product design concepts using grey-fuzzy information axiom","authors":"D. Akay, O. Kulak","doi":"10.1109/GSIS.2007.4443431","DOIUrl":"https://doi.org/10.1109/GSIS.2007.4443431","url":null,"abstract":"Evaluation of product design concepts is an important and critical problem, considering incomplete and imprecise information in the early stages of product design process. In order to solve this problem, grey theory, fuzzy sets and information axiom are combined in this study under the name of grey-fuzzy information axiom for solving product concept evaluation problem for the first time. The information axiom has the capability to solve multi-attribute evaluation problems. Grey and fuzzy set theories are complementary methods for quantification uncertainty. Applicability of the proposed method is demonstrated on the evaluation of dishwasher design concepts. It has been shown that grey-fuzzy information axiom is an appropriate tool to be used for the concept evaluation problem in case of having different types of uncertainties.","PeriodicalId":445155,"journal":{"name":"2007 IEEE International Conference on Grey Systems and Intelligent Services","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134372298","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 : 2007-11-01DOI: 10.1109/GSIS.2007.4443373
Yao-guo Dang, Sifeng Liu, Jie Song
There exists uncertain in almost problems of our practices and the uncertain hold back decision-maker cannot accurately define indices values when they evaluate the system. For this problem, present decision-maker often defines an interval number to denote this index value, but none has studied the interval number decision model in grey target decision. In this paper, the distance of the interval number, m dimension interval number and their characteristics are defined firstly, and the distance of interval number generalizes the distance of real number is proved, then, the method to normalize the interval number is developed. Based on the above, the multi-attribute decision model of grey target based on interval number is derived, which extends the grey target decision model from real number sequence to interval number sequence and riches the grey theories in grey target decision. Last, the validity and practicability are illustrated with an example.
{"title":"Study on the multi-attribute decision model of grey target based on interval numbers","authors":"Yao-guo Dang, Sifeng Liu, Jie Song","doi":"10.1109/GSIS.2007.4443373","DOIUrl":"https://doi.org/10.1109/GSIS.2007.4443373","url":null,"abstract":"There exists uncertain in almost problems of our practices and the uncertain hold back decision-maker cannot accurately define indices values when they evaluate the system. For this problem, present decision-maker often defines an interval number to denote this index value, but none has studied the interval number decision model in grey target decision. In this paper, the distance of the interval number, m dimension interval number and their characteristics are defined firstly, and the distance of interval number generalizes the distance of real number is proved, then, the method to normalize the interval number is developed. Based on the above, the multi-attribute decision model of grey target based on interval number is derived, which extends the grey target decision model from real number sequence to interval number sequence and riches the grey theories in grey target decision. Last, the validity and practicability are illustrated with an example.","PeriodicalId":445155,"journal":{"name":"2007 IEEE International Conference on Grey Systems and Intelligent Services","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132244657","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 : 2007-11-01DOI: 10.1109/GSIS.2007.4443479
Yang Ke-wu, Zhu Jin-fu, S. Qiang
In view of the actual demand of the current aviation enterprise, this paper uses ID3 classification algorithm of data mining to analyze the investigation data obtained in a waiting hall at an airport. It also points out what customer community the marketing strategy should pay attention to in the process of developing the high-end customer in the future.
{"title":"The application of ID3 algorithm in aviation marketing","authors":"Yang Ke-wu, Zhu Jin-fu, S. Qiang","doi":"10.1109/GSIS.2007.4443479","DOIUrl":"https://doi.org/10.1109/GSIS.2007.4443479","url":null,"abstract":"In view of the actual demand of the current aviation enterprise, this paper uses ID3 classification algorithm of data mining to analyze the investigation data obtained in a waiting hall at an airport. It also points out what customer community the marketing strategy should pay attention to in the process of developing the high-end customer in the future.","PeriodicalId":445155,"journal":{"name":"2007 IEEE International Conference on Grey Systems and Intelligent Services","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131696826","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 : 2007-11-01DOI: 10.1109/GSIS.2007.4443360
Sun Jinzhong
The prediction effect of GM(l,n) model is not always satisfied. The known correction methods of residual errors either need preprocess the error data to satisfy specific conditions such as non-negative, quasi-exponential law or require much more data to the train sample. Firstly, the paper improves the traditional accumulated generating operation and provides a kind of Increase accumulated generating operation (IAGO) which generates the required data sequence without high order AGO. Then, the paper proposes a kind of grey composite prediction method based on SVR where GM(1,1) model is used to predict and SVR makes the correction for the GM(l,l)'s prediction results. This method synthetically utilizes the merits of the grey system theory and SVR and thus has higher prediction precision. Especially, the paper provides a heuristic arithmetic of how to ascertain the increase coefficients and obtain the prediction values. Finally, the method is used for the medium-term or long-term forecast of regional economy and displays good application effect.
{"title":"The grey composite prediction based on support vector regression","authors":"Sun Jinzhong","doi":"10.1109/GSIS.2007.4443360","DOIUrl":"https://doi.org/10.1109/GSIS.2007.4443360","url":null,"abstract":"The prediction effect of GM(l,n) model is not always satisfied. The known correction methods of residual errors either need preprocess the error data to satisfy specific conditions such as non-negative, quasi-exponential law or require much more data to the train sample. Firstly, the paper improves the traditional accumulated generating operation and provides a kind of Increase accumulated generating operation (IAGO) which generates the required data sequence without high order AGO. Then, the paper proposes a kind of grey composite prediction method based on SVR where GM(1,1) model is used to predict and SVR makes the correction for the GM(l,l)'s prediction results. This method synthetically utilizes the merits of the grey system theory and SVR and thus has higher prediction precision. Especially, the paper provides a heuristic arithmetic of how to ascertain the increase coefficients and obtain the prediction values. Finally, the method is used for the medium-term or long-term forecast of regional economy and displays good application effect.","PeriodicalId":445155,"journal":{"name":"2007 IEEE International Conference on Grey Systems and Intelligent Services","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133434592","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 : 2007-11-01DOI: 10.1109/GSIS.2007.4443528
Junyan Zhang, Tian Jiang, Duan Gang
With the rapid growth of electronic commerce, there is growing demand and great potential for online negotiation services. Negotiation is a process between buyers and sellers in a business transaction trying to reach an agreement on one or more issues. The outcome of the negotiation depends on several parameters such as the Agents' strategies and the knowledge one Agent has about the others. It is important that an Agent chooses a proper negotiation strategy based on negotiation factors in order to achieve its maximum utility. In this paper, we first propose a negotiation model according to Agent's four factors: belief, time, competition and opportunity. Based on this model, we then present an adaptive negotiation strategy that a negotiator can use to increase its utility. The strategy adapts itself based on information obtained from the negotiation process. Our experimental results show that buyer Agent and seller Agent can obtain their maximum utilities and the best satisfaction degrees through the adaptive negotiation strategy.
{"title":"Agent-based multi-factors adaptive negotiation in E-Commerce","authors":"Junyan Zhang, Tian Jiang, Duan Gang","doi":"10.1109/GSIS.2007.4443528","DOIUrl":"https://doi.org/10.1109/GSIS.2007.4443528","url":null,"abstract":"With the rapid growth of electronic commerce, there is growing demand and great potential for online negotiation services. Negotiation is a process between buyers and sellers in a business transaction trying to reach an agreement on one or more issues. The outcome of the negotiation depends on several parameters such as the Agents' strategies and the knowledge one Agent has about the others. It is important that an Agent chooses a proper negotiation strategy based on negotiation factors in order to achieve its maximum utility. In this paper, we first propose a negotiation model according to Agent's four factors: belief, time, competition and opportunity. Based on this model, we then present an adaptive negotiation strategy that a negotiator can use to increase its utility. The strategy adapts itself based on information obtained from the negotiation process. Our experimental results show that buyer Agent and seller Agent can obtain their maximum utilities and the best satisfaction degrees through the adaptive negotiation strategy.","PeriodicalId":445155,"journal":{"name":"2007 IEEE International Conference on Grey Systems and Intelligent Services","volume":"122 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133638393","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 : 2007-11-01DOI: 10.1109/GSIS.2007.4443329
Y. Hao, Juan Du, Wei Wang, Xuemeng Wang
Economic development is a continuous and dynamic process. It can be divided into three specific components according to different time scales: the long-term trend, the medium-term periodic variation and the short-term random fluctuation. In this paper we used the grey system model to simulate the long-term trend of economic development and obtained the periodic variation from analysis of residual model. Amalgamating the long-term trend and the periodic variation, we obtained periodic correction, from which we got the random fluctuation. Using the periodic variation and the random fluctuation, the whole economic development process has been simulated through developing a predictive model. The application of the model to Shanxi Province shows that the model performs well. This model provides a new analysis method for the development planning of regional economy,which can provide the main scientific basis for the adjustment of economic structure and the economic development of Shanxi Province in the future.
{"title":"A grey system model for simulation of economic development","authors":"Y. Hao, Juan Du, Wei Wang, Xuemeng Wang","doi":"10.1109/GSIS.2007.4443329","DOIUrl":"https://doi.org/10.1109/GSIS.2007.4443329","url":null,"abstract":"Economic development is a continuous and dynamic process. It can be divided into three specific components according to different time scales: the long-term trend, the medium-term periodic variation and the short-term random fluctuation. In this paper we used the grey system model to simulate the long-term trend of economic development and obtained the periodic variation from analysis of residual model. Amalgamating the long-term trend and the periodic variation, we obtained periodic correction, from which we got the random fluctuation. Using the periodic variation and the random fluctuation, the whole economic development process has been simulated through developing a predictive model. The application of the model to Shanxi Province shows that the model performs well. This model provides a new analysis method for the development planning of regional economy,which can provide the main scientific basis for the adjustment of economic structure and the economic development of Shanxi Province in the future.","PeriodicalId":445155,"journal":{"name":"2007 IEEE International Conference on Grey Systems and Intelligent Services","volume":"685 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121987709","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 : 2007-11-01DOI: 10.1109/GSIS.2007.4443361
Liu Jian-yong, Li Ling, Zhang Yong-li, Li Yan
Traditional Grey GM(1,1) Model had its defect when it was applied to forecast relative data series. The relationship between different data series can't be reflected properly. In order to solve the problem, artificial neural network (ANN) is combined to forecast multi-series data. Then the network optimization is aided by improved genetic algorithm (GA). So the network weights and thresholds were self-adaptively evolved. Then a hybrid grey model combined with ANN and GA was put forward. Based on Matlab program, the simulation example shows that the hybrid algorithm improves the forecasting precision. It can provide effective help for forecasting work.
{"title":"A multi-series grey forecasting model based on neural network improved by genetic algorithm","authors":"Liu Jian-yong, Li Ling, Zhang Yong-li, Li Yan","doi":"10.1109/GSIS.2007.4443361","DOIUrl":"https://doi.org/10.1109/GSIS.2007.4443361","url":null,"abstract":"Traditional Grey GM(1,1) Model had its defect when it was applied to forecast relative data series. The relationship between different data series can't be reflected properly. In order to solve the problem, artificial neural network (ANN) is combined to forecast multi-series data. Then the network optimization is aided by improved genetic algorithm (GA). So the network weights and thresholds were self-adaptively evolved. Then a hybrid grey model combined with ANN and GA was put forward. Based on Matlab program, the simulation example shows that the hybrid algorithm improves the forecasting precision. It can provide effective help for forecasting work.","PeriodicalId":445155,"journal":{"name":"2007 IEEE International Conference on Grey Systems and Intelligent Services","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120945675","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 : 2007-11-01DOI: 10.1109/GSIS.2007.4443278
S. Hao, Lin Hsinyi, Da Qingli
The function of the Centralized Return Center (CRC) is illustrated and the CRC location is researched qualitatively in this paper. The index system of location assessment for CRC is conducted by analyzing influencing factors of CRC location. On the base of that, a hierarchy grey comprehensive evaluation model of CRC location is established by using hierarchy grey comprehensive evaluation method. An example demonstrates that the model can solve the problem of CRC location effectively.
{"title":"Location of centralized return center based on the grey comprehensive evaluation method","authors":"S. Hao, Lin Hsinyi, Da Qingli","doi":"10.1109/GSIS.2007.4443278","DOIUrl":"https://doi.org/10.1109/GSIS.2007.4443278","url":null,"abstract":"The function of the Centralized Return Center (CRC) is illustrated and the CRC location is researched qualitatively in this paper. The index system of location assessment for CRC is conducted by analyzing influencing factors of CRC location. On the base of that, a hierarchy grey comprehensive evaluation model of CRC location is established by using hierarchy grey comprehensive evaluation method. An example demonstrates that the model can solve the problem of CRC location effectively.","PeriodicalId":445155,"journal":{"name":"2007 IEEE International Conference on Grey Systems and Intelligent Services","volume":"13 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116819529","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 : 2007-11-01DOI: 10.1109/GSIS.2007.4443527
Kai-Zhou Gao, Z. Bao, Xiangqing Li, Dan Zhang
This paper studies on knowledge retrieval technology in product conceptual design. In this study, a two-layer retrieval technology is proposed. One is to get the similarities of function units through matching function attribute values which is weighted. The concepts of similarity vector are proposed for searching similar function units or module. Another, extended-rule and restriction matrix is proposed to depict the restrictions and constraints of problem-case and historic-cases. The similarity of restrictions between problem-case and historic-case is accounted by restriction matrix. A conceptual design knowledge retrieval framework is constructed to retrieve the design knowledge of the similar historic-case to problem-case. The framework comprises of requirement analysis, function decomposing, retrieving module of relation design knowledge and knowledge support module. Finally, an application instance for mobile telephone is shown to explain the process of knowledge support process based on case and integrated rule.
{"title":"Study on two-layer knowledge retrieval technology in conceptual design","authors":"Kai-Zhou Gao, Z. Bao, Xiangqing Li, Dan Zhang","doi":"10.1109/GSIS.2007.4443527","DOIUrl":"https://doi.org/10.1109/GSIS.2007.4443527","url":null,"abstract":"This paper studies on knowledge retrieval technology in product conceptual design. In this study, a two-layer retrieval technology is proposed. One is to get the similarities of function units through matching function attribute values which is weighted. The concepts of similarity vector are proposed for searching similar function units or module. Another, extended-rule and restriction matrix is proposed to depict the restrictions and constraints of problem-case and historic-cases. The similarity of restrictions between problem-case and historic-case is accounted by restriction matrix. A conceptual design knowledge retrieval framework is constructed to retrieve the design knowledge of the similar historic-case to problem-case. The framework comprises of requirement analysis, function decomposing, retrieving module of relation design knowledge and knowledge support module. Finally, an application instance for mobile telephone is shown to explain the process of knowledge support process based on case and integrated rule.","PeriodicalId":445155,"journal":{"name":"2007 IEEE International Conference on Grey Systems and Intelligent Services","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114805850","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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