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2009 IEEE International Conference on Grey Systems and Intelligent Services (GSIS 2009)最新文献

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The multi-attribute weighing decision model of grey target based on savage decision criteria 基于野蛮决策准则的灰色目标多属性加权决策模型
2009 IEEE International Conference on Grey Systems and Intelligent Services (GSIS 2009) Pub Date : 2009-11-01 DOI: 10.1109/GSIS.2009.5408078
Zeng Hua, Yao-guo Dang, Jie Song, Xue-mei Li
{"title":"The multi-attribute weighing decision model of grey target based on savage decision criteria","authors":"Zeng Hua, Yao-guo Dang, Jie Song, Xue-mei Li","doi":"10.1109/GSIS.2009.5408078","DOIUrl":"https://doi.org/10.1109/GSIS.2009.5408078","url":null,"abstract":"This paper studies on the multi-attribute weighing decision model of grey target based on theories of decision-making analysis. Concerning of Savage decision criteria under the circumstance of uncertain decision, grey interval number series have been put forward to extend definition of real number series as well as a ranking method has been given according to the distance from Grey target. In this case, a decision model of multi-indicator and weighing grey target is developed based on grey target decision theory. Such method provides a new approach of multi-indicator interval grey number decision. Finally, the effectiveness of the method has been verified by a real example.","PeriodicalId":294363,"journal":{"name":"2009 IEEE International Conference on Grey Systems and Intelligent Services (GSIS 2009)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130121991","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}
引用次数: 0
Hybrid genetic algorithm for travel time connectivity reliability of optimal path 最优路径旅行时间连通性可靠性的混合遗传算法
2009 IEEE International Conference on Grey Systems and Intelligent Services (GSIS 2009) Pub Date : 2009-11-01 DOI: 10.1109/GSIS.2009.5408143
D. Ma
{"title":"Hybrid genetic algorithm for travel time connectivity reliability of optimal path","authors":"D. Ma","doi":"10.1109/GSIS.2009.5408143","DOIUrl":"https://doi.org/10.1109/GSIS.2009.5408143","url":null,"abstract":"This paper researches on the problem of searching for the reliable path for transportation networks. The reliable path finding problem is concerned with searching for the path with the maximum value of connectivity reliability. In view of the literature on travel time variations, the relationship between the mean travel time and its connectivity reliability is adopted in the proposed model. In order to simplify the difficulties of the solution, this paper takes the travel time and its connectivity reliability equal to a 0–1 knapsack problem, then defines a new conception of greedy transform which is given an efficient algorithm, after combining the new greedy transform method with Genetic Algorithm, obtains Hybrid Genetic Algorithm (HGA). This algorithm (HGA) can be considered as an efficient algorithm to solve the reliable path finding problem and some other knapsack problems. Numerical results are presented to demonstrate the applications of the proposed algorithm.","PeriodicalId":294363,"journal":{"name":"2009 IEEE International Conference on Grey Systems and Intelligent Services (GSIS 2009)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130422841","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}
引用次数: 1
Measuring the delay time of Chinese employment structure based on grey incidence analysis 基于灰色关联分析的中国就业结构延迟时间测度
2009 IEEE International Conference on Grey Systems and Intelligent Services (GSIS 2009) Pub Date : 2009-11-01 DOI: 10.1109/GSIS.2009.5408337
Qingfeng Wang, Yao-guo Dang
{"title":"Measuring the delay time of Chinese employment structure based on grey incidence analysis","authors":"Qingfeng Wang, Yao-guo Dang","doi":"10.1109/GSIS.2009.5408337","DOIUrl":"https://doi.org/10.1109/GSIS.2009.5408337","url":null,"abstract":"The normal economy development requires that industrial structure and employment structure should adapt to each other. However, the change of employment structure is inconsistent with the adjustment of industry restructure in China. This paper first calculates the Moore value of Chinese industrial structure and employment structure during 1985–2006, then applies grey incidence analysis to measure the delay time of employment structure. The result indicates that grey incidence analysis can show the lag relation between industrial structure and employment structure accurately. Chinese employment structure lags behind industrial structure and the delay time is 5 years.","PeriodicalId":294363,"journal":{"name":"2009 IEEE International Conference on Grey Systems and Intelligent Services (GSIS 2009)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133997809","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}
引用次数: 1
Gray Verhulst modeling prediction and education research for Beijing SARS 北京SARS的Gray Verhulst模型预测与教育研究
2009 IEEE International Conference on Grey Systems and Intelligent Services (GSIS 2009) Pub Date : 2009-11-01 DOI: 10.1109/GSIS.2009.5408262
Yin Boming, Wang Yuanbo
{"title":"Gray Verhulst modeling prediction and education research for Beijing SARS","authors":"Yin Boming, Wang Yuanbo","doi":"10.1109/GSIS.2009.5408262","DOIUrl":"https://doi.org/10.1109/GSIS.2009.5408262","url":null,"abstract":"In 2003 year, Beijing SARS epidemic is a process of gray system, which related to government decision-making, health prevention and treatment, scientific research, transportation, architectural building of site, indigenous communities, material suppliers and so on. The published data of SARS cases from March 31th to April 18th are not allowed to incomplete data. So that the author studied the ways to fill the data into the large array, and on May 9th completion the modeling of the Beijing SARS. The model successfully predicted the cumulative eventual number of SARS cases at 2512 people (the actual number is 2521 people), about May 21th new SARS cases entered the single-digit growth stage, during the days from May 30th to June 10th entered the saturation phase of zero growth. Model prediction accuracy has reached 99.2%.","PeriodicalId":294363,"journal":{"name":"2009 IEEE International Conference on Grey Systems and Intelligent Services (GSIS 2009)","volume":"188 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134262350","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}
引用次数: 1
Stock return prediction based on Bagging-decision tree 基于bagging决策树的股票收益预测
2009 IEEE International Conference on Grey Systems and Intelligent Services (GSIS 2009) Pub Date : 2009-11-01 DOI: 10.1109/GSIS.2009.5408165
Huacheng Wang, Yanxia Jiang, Hui Wang
{"title":"Stock return prediction based on Bagging-decision tree","authors":"Huacheng Wang, Yanxia Jiang, Hui Wang","doi":"10.1109/GSIS.2009.5408165","DOIUrl":"https://doi.org/10.1109/GSIS.2009.5408165","url":null,"abstract":"There is a vast amount of financial information on companies' financial performance. This information is of great interest for different stakeholders, i.e., stockholders, creditors, auditors, financial analysts, and managers. For stakeholders it is important to extract relevant performance information of the companies they are interested in. As a common method for classification and prediction, decision tree has merits, such as intelligible, rapid, and simple. In this paper, we design a financial statement analysis using decision tree. Fifty financial ratios are selected to predict the direction of one-year-ahead earnings changes. A Bagging technique is introduced to improve the classification accuracy of decision tree. Other methods are also examined in order to make comparison. The results show that, compared with the standard-decision tree model and Boosting-decision tree model, the Bagging-decision tree model works better in stock return prediction.","PeriodicalId":294363,"journal":{"name":"2009 IEEE International Conference on Grey Systems and Intelligent Services (GSIS 2009)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131562708","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}
引用次数: 17
An improved algorithm of grey model-GM(1,1) based on total least squares and its application in deformation forecast 基于总最小二乘的改进灰色模型gm(1,1)算法及其在变形预测中的应用
2009 IEEE International Conference on Grey Systems and Intelligent Services (GSIS 2009) Pub Date : 2009-11-01 DOI: 10.1109/GSIS.2009.5408291
Lu Tieding, Zhou Shijian, Liu Wei, Zhang Liting
{"title":"An improved algorithm of grey model-GM(1,1) based on total least squares and its application in deformation forecast","authors":"Lu Tieding, Zhou Shijian, Liu Wei, Zhang Liting","doi":"10.1109/GSIS.2009.5408291","DOIUrl":"https://doi.org/10.1109/GSIS.2009.5408291","url":null,"abstract":"This paper presents an improved algorithm for grey model-GM(1,1) based on total least squares(TLS). As we know that the parameters a and b in grey model-GM(1,1) can be solved by the Least squares method. The LS method is based on an assumption that vector Y contains errors while repeated additive matrix B is accurate in GM(1,1). When we analyze the element of matrix B, the matrix B also contains errors in fact. TLS is the method of fitting that is appropriate when there are errors in both vector Y and matrix B. The calculated results of an example show that the prediction model based on TLS can enhance the prediction accuracy.","PeriodicalId":294363,"journal":{"name":"2009 IEEE International Conference on Grey Systems and Intelligent Services (GSIS 2009)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131736360","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}
引用次数: 4
Evaluation of clustered enterprises' knowledge management based on weighted grey relational model 基于加权灰色关联模型的集群企业知识管理评价
2009 IEEE International Conference on Grey Systems and Intelligent Services (GSIS 2009) Pub Date : 2009-11-01 DOI: 10.1109/GSIS.2009.5408063
Cai Youhua, Chen Guohong, Zhang Qishan
{"title":"Evaluation of clustered enterprises' knowledge management based on weighted grey relational model","authors":"Cai Youhua, Chen Guohong, Zhang Qishan","doi":"10.1109/GSIS.2009.5408063","DOIUrl":"https://doi.org/10.1109/GSIS.2009.5408063","url":null,"abstract":"The study on knowledge management (KM) evaluation is an important aspect in KM's research. On the basis of relevant literature, this paper designs an evaluation index system of clustered enterprises' KM. In view of the different importance of each factor and the evaluation of clustered enterprises' KM is pessimistic and uncertain, this paper uses weighted grey relational model to evaluate the level of KM systematically. It provides a feasible and practical approach for the quantitative evaluation of clustered enterprises' KM.","PeriodicalId":294363,"journal":{"name":"2009 IEEE International Conference on Grey Systems and Intelligent Services (GSIS 2009)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131009255","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}
引用次数: 0
Grey number operation principle based on probability distribution 基于概率分布的灰数运算原理
2009 IEEE International Conference on Grey Systems and Intelligent Services (GSIS 2009) Pub Date : 2009-11-01 DOI: 10.1109/GSIS.2009.5408297
Xu Huafeng, Fan Zhigeng
{"title":"Grey number operation principle based on probability distribution","authors":"Xu Huafeng, Fan Zhigeng","doi":"10.1109/GSIS.2009.5408297","DOIUrl":"https://doi.org/10.1109/GSIS.2009.5408297","url":null,"abstract":"In this paper a new algorithm is proposed for grey number operation in grey system theory considering probability distribution. The operation of discrete grey number and the continual grey number has been investigated extensively. Using numerical examples we explained the calculation process and the proposed method has broad application prospects in grey forecast, decision-making and grey relation analysis.","PeriodicalId":294363,"journal":{"name":"2009 IEEE International Conference on Grey Systems and Intelligent Services (GSIS 2009)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131170313","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}
引用次数: 0
Grey relational grade decision model for selection of project delivery system 项目交付系统选择的灰色关联度决策模型
2009 IEEE International Conference on Grey Systems and Intelligent Services (GSIS 2009) Pub Date : 2009-11-01 DOI: 10.1109/GSIS.2009.5408015
Liang Huimin, Wang Zhuofu
{"title":"Grey relational grade decision model for selection of project delivery system","authors":"Liang Huimin, Wang Zhuofu","doi":"10.1109/GSIS.2009.5408015","DOIUrl":"https://doi.org/10.1109/GSIS.2009.5408015","url":null,"abstract":"A construction project is oftern facing various uncertainty environments, and the product of construction is very complexity. Selecting a project delivery system is a critical task, which determines the project schedule, quality and investment objectives. This study proposes a decision- making model for the selection of project delivery system which is based on information entropy and grey relational grade analysis. In order to overcome the subjective evaluations from the experts, the theory of ‘entropy weight’ is applied to modify the experts' subjective weight. The multi-attribute grey relational grade decision-making is used to deal with the uncertainty information for selection of project delivery system. The application of the model in a real-world problem is provided. The methodology provides an effective way for the owners to select an appropriate delivery system for their project in the uncertainty condition.","PeriodicalId":294363,"journal":{"name":"2009 IEEE International Conference on Grey Systems and Intelligent Services (GSIS 2009)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130928748","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}
引用次数: 4
Regional innovation efficiency of China and its influencing factors 中国区域创新效率及其影响因素
2009 IEEE International Conference on Grey Systems and Intelligent Services (GSIS 2009) Pub Date : 2009-11-01 DOI: 10.1109/GSIS.2009.5408057
Tian Zhen-ping
{"title":"Regional innovation efficiency of China and its influencing factors","authors":"Tian Zhen-ping","doi":"10.1109/GSIS.2009.5408057","DOIUrl":"https://doi.org/10.1109/GSIS.2009.5408057","url":null,"abstract":"Based on the panel data of China's 30 regions during 1998–2005, this study conducted an empirical analysis on the regional innovation efficiency of China by using the stochastic frontier production function. Our results show that there is a distinct positive correlation between the educational level of workers and the region's innovation efficiency, and there is a distinct negative correlation between the industrial structure and the region's innovation efficiency. R&D human resources investment has a higher output elasticity compared to the R&D capital expenditure. The innovation efficiency of various areas showed a steady up-trend, and it was more closely related to the development of regional economy. The regional innovation efficiency has a tendency of convergence, indicating that the laggard regions are catching up with the advanced region.","PeriodicalId":294363,"journal":{"name":"2009 IEEE International Conference on Grey Systems and Intelligent Services (GSIS 2009)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132689816","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}
引用次数: 0
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