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🏛️國立陽明交通大學機構典藏

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    A web-based monitor and management system architecture for enterprise Virtual Private Network
    (2005-01-01)
    Chen, RS
    ;
    Chang, CC
    ;
    Yeh, SW
    ;
    資訊管理與財務金融系 註：原資管所+財金所
    ;
    Department of Information Management and Finance
    This research is based on the new network management technologies such as Policy-based Network Management, Mobile Agent, etc., to design a VPN monitor and management system architecture that is suitable for the enterprise use and contains high level management with low Network Traffic load. This system architecture integrates the monitor and management for both VPN devices and general network devices, such the feature makes enterprise can integrate the monitor and manage the VPN and Intranet at the same time and solve the problems caused by using the VPN. The results of this research provide a VPN system architecture for monitoring and managing the enterprises and establish a prototype for the enterprise VPN` monitor and management system.
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    A heuristic approach to generating file spanning trees for reliability analysis of distributed computing systems
    (1997-11-01)
    Chen, DJ
    ;
    Chen, RS
    ;
    Huang, TH
    ;
    資訊科學與工程研究所
    ;
    Institute of Computer Science and Engineering
    The reliability of Distributed Computing Systems (DCS) in terms of Distributed Program Reliability (DPR) and Distributed System Reliability (DSR) has been studied intensively. Current reliability algorithms available for the analysis of DPR and DSR include MFST, FARE, FST, and FST-SPR. This paper presents a reliability algorithm, called HRFST, that eliminates the need to search a spanning tree during each subgraph generation. The HRFST algorithm reduces both the number of subgraphs (or trees) generated and the actual execution time required for analysis of DPR and DSR. Examination of several sample cases shows that the HRFST algorithm is more efficient than the FST-SPR algorithm.
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    A fuzzy data mining algorithm for finding sequential patterns
    (2003-04-01)
    Hu, YC
    ;
    Chen, RS
    ;
    Tzeng, GH
    ;
    Shieh, JH
    ;
    科技管理研究所
    Since fuzzy knowledge representation can facilitate interaction between an expert system and its users, the effective construction of a fuzzy knowledge base is important. Fuzzy sequential patterns described by natural language are one type of fuzzy knowledge representation, and can thus be helpful in building a prototype fuzzy knowledge base. We define that a fuzzy sequence is an ordered fist of frequent fuzzy grids, and the length of a fuzzy sequence is the number of frequent fuzzy grids in the frequent fuzzy sequence. Frequent fuzzy grids and frequent fuzzy sequences can be determined by comparing individual fuzzy supports with the user-specified minimum fuzzy support. A fuzzy sequential pattern is just a frequent fuzzy sequence, but it is not contained in any other frequent fuzzy sequence. In this paper, an effective algorithm called the Fuzzy Grids Based Sequential Patterns Mining Algorithm (FGBSPMA) is proposed to generate fuzzy sequential patterns. A numerical example is used to show an analysis of the user visit to websites, demonstrating the usefulness of the proposed algorithm.
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    Design an intelligent CIM system based on data mining technology for new manufacturing processes
    (2004)
    Wu, RC
    ;
    Chen, RS
    ;
    Fan, CR
    ;
    資訊管理與財務金融系 註：原資管所+財金所
    ;
    Department of Information Management and Finance
    The purpose of this paper is to explain a specific intelligent CIM (computer integrated manufacturing) system by integrating the following five major subject areas: computer integrated manufacturing, data warehouse, online analytical processing (OLAP), data mining and artificial intelligence. The data mining system makes use of the decision tree algorithm and classification model in exploring the meaningful information, which is useful in the process of decision making. Subsequently, the rules discovered by the data mining system are expressed through the rule based knowledge presentation method of the expert system. The intelligent CIM system is applied to semiconductor packing factories and also point at the great fluctuation of DRAM (dynamic random access memory) prices. The results of this paper are the product yield, the manufacturing cycle time and the frequency of holding lot, which have been improved. The contribution can increase business competitiveness, reduce production cost, and promote the rate of available promise for order.
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    ACTAM: Cooperative multi-agent system architecture for urban traffic signal control
    (2005-01-01)
    Chen, RS
    ;
    Chen, DK
    ;
    Lin, SY
    ;
    資訊管理與財務金融系 註：原資管所+財金所
    ;
    Department of Information Management and Finance
    The traffic congestion problem in urban areas is worsening since traditional traffic signal control systems cannot provide] efficient traffic regulation. Therefore, dynamic traffic signal control in Intelligent Transportation System (ITS) recently has received increasing attention. This study devised a multi-agent architecture, the Adaptive and Cooperative Traffic light Agent Model (ACTAM), for a decentralized traffic signal control system. The proposed architecture comprises a data Storage and communication layer, a traffic regulation factor processing layer, and a decision-making layer. This study focused on utilizing the cooperation of multi-agents and the prediction mechanism of our architecture, the Forecast Module, to forecast future traffic volume in each individual intersection. The Forecast Module is designed to forecast traffic volume in an intersection via multi-agent cooperation by exchanging traffic volume information for adjacent intersections, since vehicles passing through nearby intersections were believed to significantly influence the traffic volume of specific intersections. The proposed architecture can achieve dynamic traffic signal control. Thus, total delay time of the traffic network under ACTAM can be reduced by 37% compared to the conventional fixed sequence traffic signal control strategy. Consequently, traffic congestion in urban areas can be alleviated by adopting ACTAM.
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    A genetic algorithm for the reliability optimization of a distributed system
    (1998)
    Chen, RS
    ;
    Chu, CC
    ;
    Yeh, YS
    ;
    資訊管理與財務金融系 註：原資管所+財金所
    ;
    Department of Information Management and Finance
    The widespread use of distributed system(DS) over the centralized systems can be attributed partially to its potential to enhance system reliability. In the reliability analysis of a DS, S-node Reliability(SNR) is defined as the probabilities that all nodes in S(a subset of all processing elements) are connected. SNR optimization for the distributed systems Exact Method(EM) has received only limited attention. Owing to the fact that computing reliability of DS is in general an NP-hard problem. Genetic Algorithms(GA) are search techniques for global optimization in a complex search space. GA can be applied to search a large, multimodel, complex problem spaces. Thus, there is a good potential to obtain optimal and near optimal results using GA for network reliability problem. In this work, we attempt to reduce computational time and complexity by presenting a method based on a Genetic Algorithm S-Node set Reliability Methodology (CASNR) to optimize a specified object function under a given capacity constraints. The versatility of genetic algorithm is illustrated by applying it to solve the S-node set reliability problem. Using GASNR to find the best S-node sets. Because the final number of best S-node sets is only one, we just take less time to compute the reliability using SYREL. In addition, the proposed algorithm is compared with the existing one for various topologies. Those results demonstrate that for a large DS, the proposed algorithm is more efficient in execution time.
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    Discovery of fuzzy sequential patterns for fuzzy partitions in quantitative attributes
    (2001)
    Chen, RS
    ;
    Tzeng, GH
    ;
    Chen, CC
    ;
    Hu, YC
    ;
    資訊管理與財務金融系 註：原資管所+財金所
    In this paper we propose the Fuzzy Grids Based Sequential Patterns Mining Algorithm (FGBSPMA) to generate all fuzzy sequential patterns from relational database. In FGBSPMA, each quantitative attribute is viewed as a linguistic variable, and can be divided into many candidate 1-dim fuzzy grids. FGBSPMA is consisted of two phases: one is to generate all the large 1-fuzzy sequences, the other is to generate all the fuzzy sequential patterns. FGBSPMA is a efficiently fuzzy sequential patterns mining algorithm, because FGBSPMA scans database only once and applies proper operations on rows of tables to generate large fuzzy sequences and fuzzy sequential patterns. An example is given to illustrate a detailed process for mining the fuzzy sequential patterns from a specified relation. From this example, we can show efficiency and usefulness of FGBSPMA.
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    A Web-based data extraction system for supply chain management-using SAP R/3
    (2002)
    Chen, RS
    ;
    Wang, HC
    ;
    Wang, CM
    ;
    資訊管理與財務金融系 註：原資管所+財金所
    ;
    Department of Information Management and Finance
    This paper presents a prototype of logistics flows and information extraction system between customers and vendors by using World Wide Web (WWW), XML with SAP R/3 programming technology (ABAP/4 Language). Three kinds of benefits are approved for most of the supply chain system. ( 1) To resolve the SAP SAPLPD performance issue existing in the Multi-Bytes Character Print with SAPWIN by developing a HTML Layout Set for the report printout. ( 2) To support business process improvement for customer services, logistics, planning and manufacturing through XML data interface embedded in the software solutions. ( 3) To provide a reliable and scalable information technology infrastructure which could fulfill the requirements of data transparency and data consistency. The result of this paper, we demonstrate an open architecture of data extraction method. It can be used in data transparency and data consistency for a supply chain. Enterprise within multi database can improve the performance of information flows. It can solve data printing problem in many types of layout set to meet the demand of enterpris.
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    Using data mining technology to design an intelligent CIM system for IC manufacturing
    (2005)
    Chen, RS
    ;
    Wu, RC
    ;
    Chang, CC
    ;
    資訊管理與財務金融系 註：原資管所+財金所
    ;
    Department of Information Management and Finance
    This paper aims to explain a specific intelligent computer integrated manufacturing system by integrating the following five major domains: computer integrated manufacturing, data warehouse, online analytical processing, data mining and artificial intelligence. The data mining system makes use of the decision tree algorithm and classification model in exploring the meaningful information, which is useful in the process of decision making. Subsequently, the rules discovered by the data mining system are expressed through the rule based knowledge presentation method of the expert system. The intelligent CIM system is applied to semiconductor packing factories and also point at the great fluctuation of dynamic random access memory prices. The contribution can increase business competitiveness, reduce production cost, and promote the rate Of available promise for order.
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    Data mining application in customer relationship management of credit card business
    (2005)
    Wu, RC
    ;
    Chen, RS
    ;
    Chang, CC
    ;
    Chen, JY
    ;
    資訊管理與財務金融系 註：原資管所+財金所
    First, we classify the selected customers into clusters using RFM model to identify high-profit, gold customers. Subsequently, we carry out data mining using association rules algorithm. We measure the similarity, difference and modified difference of mined association rules based on three rules, i.e. Emerging Patten Rule, Unexpected Change Rule, and Added/Perished Rule. In the meantime, we use rule matching threshold to derive all types of rules and explore the rules with significant change based on the degree of change measured. In this paper, we employ data mining tools and effectively discover the current spending pattern of customers and trends of behavioral change, which will allow management to detect in a large database potential changes of customer preference, and provide as early as possible products and services desired by the customers to expand the clientele base and prevent customer attrition.