Browsing by Author "Chen, RS"

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A case study in the design of BTO/CTO shop floor control system
(2003-10-01)
Chen, RS
;
Lu, KY
;
Yu, SC
;
Tzeng, HW
;
Chang, CC
Although computerized information systems are conventionally used to control production, applying a manual approach and improper logistical assignments typically reduces operating efficiency and increases customer service response time. Satisfying the requirements of remaining competitiveness in the current marketplace, such as offering build-to-order (BTO) or configuration-to-order (CTO) services is difficult. This study presents an integrated information system for use in shop floor controlling systems (SFCS) for kitting parts, producing goods, packing finished goods and distributing them, to enhance the performance of the BTO/CTO production system. Several information technologies and devices, such as barcode system, the electronic pick-to-light picking system, electronic Kanban (eKanban), and others are adopted to support the relevant logistics. A personal computer (PC) manufacturer is used to demonstrate the proposed system. The findings of the study reveal that the proposed information system can respond to the status of the production line in real time. This responsiveness can help the production controller to make a suitable decision and quickly meet the requirements of the BTO/CTO production system. (C) 2003 Elsevier Science B.V. All rights reserved.
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.
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.
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.
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.
A hybrid genetic algorithm approach on multi-objective of assembly planning problem
(2002-09-01)
Chen, RS
;
Lu, KY
;
Yu, SC
;
資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
In practice, modeling an assembly system often requires assigning a set of operations to a set of workstations. The aim is to optimize some performance indices of an assembly line. This assignation is usually a tedious design procedure so a significant amount of manpower is required to obtain a good work plan. Poor assembly planning may significantly increase the cost of products and reduce productivity. However, these optimization problems fall into the class of NP-hard problems. Finding an optimal solution in an acceptable time is difficult, even using a powerful computer. This study presents a hybrid genetic algorithm approach to the problems of assembly planning with various objectives, including minimizing cycle time, maximizing workload smoothness, minimizing the frequency of tool change, minimizing the number of tools and machines used, and minimizing the complexity of assembly sequences. A self-tuning method was developed to correct infeasible-chromosomes. Several examples were employed to illustrate the proposed approach. Experimental results indicated that the proposed method can efficiently yield many alternative assembly plans to support the design and operation of a flexible assembly system. (C) 2003 Elsevier Science Ltd. All rights reserved.
A novel method for discovering fuzzy sequential patterns using the simple fuzzy partition method
(2003-05-01)
Chen, RS
;
Hu, YC
;
資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
Sequential patterns refer to the frequently occurring patterns related to time or other sequences, and have been widely applied to solving decision problems. For example, they can help managers determine which items were bought after some items had been bought. However, since fuzzy sequential patterns described by natural language are one type of fuzzy knowledge representation, they are helpful in building a prototype fuzzy knowledge base in a business. Moreover, each fuzzy sequential pattern consisting of several fuzzy sets described by the natural language is well suited for the thinking of human subjects and will help to increase the flexibility for users in making decisions. Additionally, since the comprehensibility of fuzzy representation by human users is a criterion in designing a fuzzy system, the simple fuzzy partition method is preferable. In this method, each attribute is partitioned by its various fuzzy sets with pre-specified membership functions. The advantage of the simple fuzzy partition method is that the linguistic interpretation of each fuzzy set is easily, obtained. The main aim of this paper is exactly to propose a fuzzy data mining technique to discover fuzzy sequential patterns by using the simple partition method. Two numerical examples are utilized to demonstrate the usefulness of the proposed method.
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.
A Web-based monitor and management system architecture for enterprise virtual private network
(2005-11-01)
Chen, RS
;
Hsu, CJ
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Chang, CC
;
Yeh, SW
;
資訊管理與財務金融系註：原資管所+財金所
Virtual private network (VPN) not only possesses the low cost, inexpensive fees, and excellent support advantages of the Internet, it also has the benefit of the security as the leased line. How to properly manage the VPN is an issue in which the enterprise IT engineers have to take seriously. 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 contains high level management with low network traffic load. This system architecture integrates both VPN devices and general network devices, such the feature can integrate the monitor and manage the VPN and Intranet at the same time. The result of this research provides enterprises with a VPN architecture for monitoring and managing the enterprises, as well as to establish a prototype for the enterprise VPN monitor and management system. Such system architecture can effectively assist the semiconductor companies to monitor and manage their enterprise VPN in order to utilize the Internet resources, and to reduce the possible operation off time. The prototype system could proof the feasibility of the systematic architecture, it can automatically detect and activate the backup mechanism according to the preset management policy, and to achieve the effective and fast solution for the enterprise network problems. (c) 2005 Elsevier Ltd. All rights reserved.
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.
Acquisition of compound skills and learning costs for expanding competence sets
(2003-09-01)
Hu, YC
;
Chen, RS
;
Tzeng, GH
;
Chiu, YJ
;
科技管理研究所
For each decision problem, there is a competence set consisting of ideas, knowledge, information, and skills for solving that problem. When decision makers have not acquired the competence set, it is more difficult for them to make decisions. In order to effectively acquire a needed competence set to cope with the problem they face, finding an appropriate learning sequence for acquiring needed single skills for decision makers, the so-called competence set expansion, is very necessary. A compound skill represents a collection of single skills that might be acquired, and some useful compound skills can be added to the needed competence set to help acquire some single skills. To effectively expand the competence set, effective acquisitions of compound skills and learning costs are both necessary. This paper thus proposes a data mining technique to extract potentially useful compound skills from single skills. Subsequently, an effective method is proposed to obtain the learning cost between any two skills. A computer simulation is employed to further show that it is feasible to use those potentially useful compound skills to facilitate the acquisition of single skills through a known integer programming method for expanding the competence set. (C) 2003 Elsevier Ltd. All rights reserved.
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.
Assessing weights of product attributes from fuzzy knowledge in a dynamic environment
(2004-04-01)
Hu, YC
;
Hu, JS
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Chen, RS
;
Tzeng, GH
;
科技管理研究所
Fuzzy knowledge of consumers' frequent purchase behaviors can be extracted from transaction databases. To effectively supporting decision makers, it is necessary to use fuzzy knowledge to assess weights or degrees of consumers' attentiveness to product attributes. From the standpoint of habitual domains, frequent purchase behaviors can be viewed as ideas that are contained in the reachable domain of customers. In addition, this reachable domain is changeable with time, due to the dynamic environment. This paper thus proposes a two-phase learning method with adaptive capability. The first phase builds a fuzzy knowledge base by discovering frequent purchase behaviors from transaction databases; the second phase finds weights of product attributes by a single-layer perceptron neural network. Indeed, customers are asked to evaluate alternatives and attributes through questionnaire. Then, each alternative can be transformed into a piece of input training data for the neural network by the fuzzy knowledge base and part-worths of attributes' levels. After completing the training task, we can find weights from connection weights. Simulation results demonstrate that the proposed methods can use fuzzy knowledge to effectively find customers' attentive degrees of attributes. (C) 2002 Elsevier B.V. All rights reserved.
Data mining application in customer relationship management of credit card business
(2005)
Wu, RC
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Chen, RS
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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.
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.
Design of a full text image Chinese CD-ROM database retrieval system in a campus digital library
(2002)
Chen, RS
;
Chen, 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
The library CD-ROM database with its enormous storage and retrieving from network capabilities, has been gradually replacing some of its printed counterparts. But one of the disadvantages is that it can only access the full-text image CD-ROM database via local area network environment. This paper proposes a new method to solve this problem. The method uses hash function as data structure and image document process technique to perform a practical library full-text image CD-ROM database retrieving system. The results of its function can reduce users storage space, allow multi-users to retrieve the same CD-ROM database, and allow users to retrieve and print out full text image CD-ROM database via campus network.
Developing an XML framework for an electronic document delivery system
(2001)
Yu, SC
;
Chen, RS
;
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 Internet has forced libraries to consider how to assist users to rapidly retrieve information. Such a consideration has accelerated the development of electronic publishing and has positioned the library as mediator between users and providers: archiving information circulation and providing secure copyright clearance through an efficient electronic document delivery and payment mechanism. This work develops an Extensible Markup Language (XML) framework for electronic document delivery that offers a novel electronic document delivery system and also locates publishers who can provide the copyrighted material in an electronic format via the OPAC. The proposed electronic document delivery system has four functions: (1) it enables the electronic document payment; (2) it shortens the time between inquiry and electronic document retrieval; (3) it anticipates the changing role of libraries; and (4) it reduces the printed collection load of libraries.
Discovering fuzzy association rules using fuzzy partition methods
(2003-04-01)
Hu, YC
;
Chen, RS
;
Tzeng, GH
;
科技管理研究所
;
Institute of Management of Technology
Fuzzy association rules described by the natural language are well suited for the thinking of human subjects and will help to increase the flexibility for supporting users in making decisions or designing the fuzzy systems. In this paper, a new algorithm named fuzzy grids based rules mining algorithm (FGBRMA) is proposed to generate fuzzy association rules from a relational database. The proposed algorithm consists of two phases: one to generate the large fuzzy grids, and the other to generate the fuzzy association rules. A numerical example is presented to illustrate a detailed process for finding the fuzzy association rules from a specified database, demonstrating the effectiveness of the proposed algorithm. (C) 2002 Elsevier Science B.V. All rights reserved.
Discovery of fuzzy sequential patterns for fuzzy partitions in quantitative attributes
(2001)
Chen, RS
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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.
Finding fuzzy classification rules using data mining techniques
(2003-01-01)
Hu, YC
;
Chen, RS
;
Tzeng, GH
;
科技管理研究所
;
資訊管理與財務金融系註：原資管所+財金所
Data mining techniques can be used to discover useful patterns by exploring and analyzing data, so, it is feasible to incorporate data mining techniques into the classification process to discover useful patterns or classification rules from training samples. This paper thus proposes a data mining technique to discover fuzzy classification rules based on the well-known Apriori algorithm. Significantly, since it is difficult for users to specify the minimum fuzzy support used to determine the frequent fuzzy grids or the minimum fuzzy confidence used to determine the effective classification rules derived from frequent fuzzy grids, therefore the genetic algorithms are incorporated into the proposed method to determine those two thresholds with binary chromosomes. For classification generalization ability, the simulation results from the iris data and the appendicitis data demonstrate that the proposed method performs well in comparison with other classification methods. (C) 2002 Elsevier Science B.V. All rights reserved.