{"title":"An efficient heuristic based university timetabling/scheduling","authors":"A. Rajesh, M. Padmini, K. Athre","doi":"10.1109/GSIS.2009.5408198","DOIUrl":"https://doi.org/10.1109/GSIS.2009.5408198","url":null,"abstract":"The University Timetabling problem for a multicampus university is a challenging proposition especially where the faculty is a shared resource amongst campuses. To cater to this problem, a hierarchical heuristic solution is proposed. The heuristic solution is based on the concept of a timeslot that uses the principle of ‘correctness by design’. The constraints are handled by administrative processes at various levels of the hierarchy. A web based Java application facilitates concurrent use by multiple users across campuses and generates the timetable in constant time. Ways to handle the constraints and related sub-constraints, with ease, are discussed.","PeriodicalId":294363,"journal":{"name":"2009 IEEE International Conference on Grey Systems and Intelligent Services (GSIS 2009)","volume":"58 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":"126368686","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}
{"title":"Operational risk measurement via the loss distribution approach","authors":"Jichuang Feng, Jianming Chen, Jianping Li","doi":"10.1109/GSIS.2009.5408197","DOIUrl":"https://doi.org/10.1109/GSIS.2009.5408197","url":null,"abstract":"In the Basel II Accord, banks are encouraged to use the Advanced Measurement Approach (AMA), which is suitable for banks to assess operational risk capital, but banks are required to demonstrate their ability to capture severe tail loss events. In this paper, based on the 860 operational risk loss data of Chinese commercial banks collected from public reports from 1995 to 2006, we found that the sample data set is characterized as having heavier tail than normal distribution. Then we use loss distribution approach (LDA) to measure the operational risk and operational risk capital of Chinese commercial banks. Next, we compare operational risk economic capital of Chinese commercial banks with operational risk economic capital (EC) of other major banks. We discover that the operational risk of Chinese commercial banks is larger than that of some foreign major commercial banks.","PeriodicalId":294363,"journal":{"name":"2009 IEEE International Conference on Grey Systems and Intelligent Services (GSIS 2009)","volume":"85 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":"126039124","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}
{"title":"Application of grey relational clustering and CGNN in analyzing stability control of surrounding rocks in deep entry of coal mine","authors":"Wanbin Yang, Zhiming Qu","doi":"10.1109/GSIS.2009.5408324","DOIUrl":"https://doi.org/10.1109/GSIS.2009.5408324","url":null,"abstract":"With combination of grey neural network (CGNN) and grey relational clustering, the models are constructed, which are used to solve the prediction and comparison of surrounding rocks stability controlling parameters in deep entry of coal mine. The results show that grey relational clustering is an effective way and CGNN has perfect ability to be studied in a short-term prediction. Combined grey neural network has the features of trend and fluctuation while combining with the time-dependent sequence prediction. It is concluded that great improvements compared with any methods of trend prediction and simple factor in combined grey neural network is stated and described in stably controlling the surrounding rocks in deep entry.","PeriodicalId":294363,"journal":{"name":"2009 IEEE International Conference on Grey Systems and Intelligent Services (GSIS 2009)","volume":"23 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":"114191065","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}
{"title":"Analysis of southern Jiangsu economic growth factors based on grey production function model","authors":"Xu Ning, Dang Yaoguo, Shi Yuting","doi":"10.1109/GSIS.2009.5408036","DOIUrl":"https://doi.org/10.1109/GSIS.2009.5408036","url":null,"abstract":"Since traditional Cobb-Douglas production function cannot be supposed to great fluctuant data, this paper uses grey system GM(1,1) model to pre-deal with the raw data and establish grey production function model (model G-C-D) based on the GM(1,1) simulated sequences. This model is used to empirically analyze the role and its change of contribution factors(labor force, investment, technology progress)of Southern Jiangsu economic development from 2000 to 2007. Result shows clearly that technology progress factor is accounted for 50% above, but with a declining trend. However, capital factor shows obvious ascending trend. Finally, it explains this result and makes suggestions.","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":"116094902","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}
{"title":"An application of GRA to analyze the credit risk in banking industry","authors":"Shun-Jyh Wu, Shu-Ling Lin, Hsiu-Lan Ma, Der-Bang Wu","doi":"10.1109/GSIS.2009.5408141","DOIUrl":"https://doi.org/10.1109/GSIS.2009.5408141","url":null,"abstract":"This study proposes a new approach for analyzing the credit risks of banking industry based the modeling of Grey Relational Analysis (GRA). In order to construct a financial distress warning system for banking industry, a GRA approach is developed and applied to the real data set with 111 samples. The results of the current model are compared to those of traditional ones. The results illustrate that in the prediction of financially distress as well as financially sound banks, the proposed GRA model demonstrates better prediction accuracy than the conventional ones. The results also imply that the financial data set one year before the crisis leads to the best accuracy. It is helpful for the establishment of early warning models of financial crisis. The current results show that the proposed GRA provides a novel approach in handling financial distress warning tasks.","PeriodicalId":294363,"journal":{"name":"2009 IEEE International Conference on Grey Systems and Intelligent Services (GSIS 2009)","volume":"36 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":"116654943","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}
{"title":"Bayesian network with Grey entropy data pre-processing for modeling students' learning status","authors":"Tien-Yu Hsieh, Bor-Chen Kuo, Rih-Chang Chao, Shin-I Yeh, Pei-Chieh Chen","doi":"10.1109/GSIS.2009.5408263","DOIUrl":"https://doi.org/10.1109/GSIS.2009.5408263","url":null,"abstract":"In this paper, our study aimed to use Grey entropy to help decide which attributes, so called items in educational assessment, should be eliminated to prevent the Bayesian network modeling process from over-fitting and to obtain better accuracy. Although Bayesian network is proving to be the best technology available for diagnosing students' learning status in educational assessment, in the process of constructing a Bayesian network, the criteria of selecting testing attributes such as items or tasks will influence the diagnosing accuracy. Experiment results indicats that the Bayesian network with Grey entropy data pre-processing obtains the better more than 10% in accuracy than the man-made Bayesian network.","PeriodicalId":294363,"journal":{"name":"2009 IEEE International Conference on Grey Systems and Intelligent Services (GSIS 2009)","volume":"19 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":"125280814","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}
{"title":"Study on the relationship between the energy consumption and economic system of Jiangsu Province base on grey relational analysis","authors":"S. Licheng, Hu Ronghua","doi":"10.1109/GSIS.2009.5408328","DOIUrl":"https://doi.org/10.1109/GSIS.2009.5408328","url":null,"abstract":"This paper applies the grey relational analysis to measure the grey relational degree between the energy consumption and the economic system from 2000 to 2007. The results show that the fixed asset investment of the economic system is the major factor which results in a rapid growth of the energy consumption; the grey relational degree between coal consumption and economic system is greater than the degree between the crude oil or natural gas and economic system, and it indicates that the economic development of Jiangsu Province is still in an extensive growth mode; the grey relation between natural gas consumption and economic system is smaller, however, it is an important guarantee for the rapidly economic growth of Jiangsu Province.","PeriodicalId":294363,"journal":{"name":"2009 IEEE International Conference on Grey Systems and Intelligent Services (GSIS 2009)","volume":"81 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":"133197392","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}
{"title":"The interval forecasting method based on non-equidistant GM(1,1) with application to regional grain production","authors":"Li Bing-jun, He Chun-hua","doi":"10.1007/978-3-642-13938-3_28","DOIUrl":"https://doi.org/10.1007/978-3-642-13938-3_28","url":null,"abstract":"","PeriodicalId":294363,"journal":{"name":"2009 IEEE International Conference on Grey Systems and Intelligent Services (GSIS 2009)","volume":"23 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":"133469841","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}
{"title":"The balancing between E-commerce logistics cost and service quality based on value engineering approach","authors":"Chuanmin Mi, Yuanyuan Wang, Tingting Ma","doi":"10.1109/GSIS.2009.5408112","DOIUrl":"https://doi.org/10.1109/GSIS.2009.5408112","url":null,"abstract":"With the rapid development of E-commerce and increasing use of modern technology such as GPS and REID in logistics, E-commerce logistics has gradually become prevailing. Customers always expect logistics service quality gets significantly improved, whereas its cost should be substantially reduced. However, these two objectives are at some extent contradictory. The further the service quality improves, the higher the logistics cost. So it is an important issue to find a balance between them in managing and operating logistics. In this paper, we first analyze the characteristics of current E-commerce logistics and its service innovations in threefold: concept, content, and mode. Based on the Value Engineering theory, we study the balance between the E-commerce logistics cost and the quality of service. A simple case study is also provided.","PeriodicalId":294363,"journal":{"name":"2009 IEEE International Conference on Grey Systems and Intelligent Services (GSIS 2009)","volume":"347 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":"134289874","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}
{"title":"A comparative analysis of discretization algorithms for data mining","authors":"Xie Ming, Xinping Xiao","doi":"10.1109/GSIS.2009.5408138","DOIUrl":"https://doi.org/10.1109/GSIS.2009.5408138","url":null,"abstract":"In this paper, four kinds of typical discretization algorithms were comparatively analyzed from two aspects using examples: one referred to the variable quality of classification and accuracy of approximation under different parameter, the other was the similarity degrees between reducted variable sets and the original variable set. On determination of reducted variable sets, the reduction was regarded as multi-objective optimization problem, which was solved by the genetic algorithm, and the optimal reducted variable sets were found through including degrees. Finally, the consistent conclusion on preference of discretization algorithms was gained.","PeriodicalId":294363,"journal":{"name":"2009 IEEE International Conference on Grey Systems and Intelligent Services (GSIS 2009)","volume":"42 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":"133074139","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}