• Title/Summary/Keyword: Rule-based Systems

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A Scheme for Protecting Security Rules in Intrusion Detection System (침입 탐지 시스템을 위한 효율적인 룰 보호 기법)

  • 손재민;김현성;부기동
    • Journal of Korea Society of Industrial Information Systems
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    • v.8 no.4
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    • pp.8-16
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    • 2003
  • This paper moses a method to solve the weakness in Snort, the network based intrusion detection system. Snort which is the rule-based intrusion detection system dose not supports a protection method for their own rules which are signatures to detect intrusions. Therefore the purpose of this paper is to provide a scheme for protecting rules. The system with the proposed scheme could support integrity and confidentiality to the rules.

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Advanced Self-organizing Neural Networks with Fuzzy Polynomial Neurons : Analysis and Design

  • Oh, Sung-Kwun;Lee , Dong-Yoon
    • KIEE International Transaction on Systems and Control
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    • v.12D no.1
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    • pp.12-17
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    • 2002
  • We propose a new category of neurofuzzy networks- Self-organizing Neural Networks(SONN) with fuzzy polynomial neurons(FPNs) and discuss a comprehensive design methodology supporting their development. Two kinds of SONN architectures, namely a basic SONN and a modified SONN architecture are dicussed. Each of them comes with two types such as the generic and the advanced type. SONN dwells on the ideas of fuzzy rule-based computing and neural networks. Simulation involves a series of synthetic as well as experimental data used across various neurofuzzy systems. A comparative analysis is included as well.

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The Study of Predictive Diagnosis Technology Development Status and Promotion Plan for Reactor Coolant Pump (원자로냉각재펌프 예측진단 기술개발 현황 및 추진방안)

  • Hee Chan Kim
    • Transactions of the Korean Society of Pressure Vessels and Piping
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    • v.19 no.1
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    • pp.44-51
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    • 2023
  • The RCP is one of the main components in nuclear power plants and plays an important role in circulating coolant to the RCS system. Currently, nuclear plants are monitored using various monitoring systems. However, since they operate independently according to their functional purpose, it is not able to analyze vibration and operation/performance information comprehensively, and thus failure diagnosis accuracy is limited. In addition, these systems do not provide some important information (such as fault type, parts and cause) necessary for emergency actions, but provide only alarm information. To improve these technical problems, this study proposes a diagnosis technique (M/L, Rule-based model, Data-driven model, Narrow band model) and methodology for comprehensive analysis.

Development of a Knowledge-Based Job Shop Scheduler Applying the Attribute-Oriented Induction Method and Simulation (속성지향추론법과 시뮬레이션을 이용한 지식기반형 Job Shop 스케쥴러의 개발)

  • 한성식;신현표
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.21 no.48
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    • pp.213-222
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    • 1998
  • The objective of this study is to develop a knowledge-based scheduler applying simulation and knowledge base. This study utilizes a machine induction to build knowledge base which enables knowledge acquisition without domain expert. In this study, the best job dispatching rule for each order is selected according to the specifications of the order information. And these results are built to the fact base and knowledge base using the attribute-oriented induction method and simulation. When a new order enters in the developed system, the scheduler retrieves the knowledge base in order to find a matching record. If there is a matching record, the scheduling will be carried out by using the job dispatching rule saved in the knowledge base. Otherwise the best rule will be added to the knowledge base as a new record after scheduling to all the rules. When all these above steps finished the system will furnish a learning function.

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A Study on the Korean Text-to-Speech Using Demisyllable Units (반음절단위를 이용한 한국어 음성합성에 관한 연구)

  • Yun, Gi-Sun;Park, Sung-Han
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.27 no.10
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    • pp.138-145
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    • 1990
  • This paper present a rule-based speech synthesis method for improving the naturalness of synthetic speech and using the small data base based on demisyllable units. A 12-pole Linear Prediction Coding method is used to analyses demisyllable speech signals. A syllable and vowel concatenation rule is developed to improve the naturalness and intelligibility of the synthetic speech. in addiion, phonological structure transform rule using neural net and prosody rules are applied to the synthetic speech.

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Design of fuzzy PID controller for based on PI and PD parallel structure

  • Lee, Chul-Heui;Kim, Kwang-Ho;Seo, Seon-Hak
    • 제어로봇시스템학회:학술대회논문집
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    • 1995.10a
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    • pp.71-74
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    • 1995
  • In this paper, a new PID fuzzy controller(FC) based on parallel operation of PI and PD fuzzy control is presented. First, two fuzzy rule bases are constructed by separating the linguistic control rule for PID FC into two parts : one is e-.DELTA.e part, and the other is .DELTAL.$^{2}$e-.DELTA.e part. And then two FCs employing these rule bases indivisually are synthesized and run in parallel. The incremental control input is determined by taking weighted mean of the outputs of two FCs. The proposed PID FC improves the transient response of the system and gives better performance than the conventional PI FC.

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A Personalized Recommender based on Collaborative Filtering and Association Rule Mining

  • Kim Jae Kyeong;Suh Ji Hae;Cho Yoon Ho;Ahn Do Hyun
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2002.05a
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    • pp.312-319
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    • 2002
  • A recommendation system tracks past action of a group of users to make a recommendation to individual members of the group. The computer-mediated marking and commerce have grown rapidly nowadays so the concerns about various recommendation procedure are increasing. We introduce a recommendation methodology by which Korean department store suggests products and services to their customers. The suggested methodology is based on decision tree, product taxonomy, and association rule mining. Decision tree is to select target customers, who have high purchase possibility of recommended products. Product taxonomy and association rule mining are used to select proper products. The validity of our recommendation methodology is discussed with the analysis of a real Korean department store.

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Intelligent Anti-Money Laundering Systems Development for the Korea Financial Intelligence Unit

  • Shin Kyung-Shik;Kim Hyun-Jung;Lee In-Ho;Kim Hyo-Sin;Kim Jae-Sik
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2006.06a
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    • pp.294-300
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    • 2006
  • This case study shows constructing the knowledge-based system using a rule-based approach for detecting transactions regarding money laundering in the Korea Financial Intelligence Unit (KoFIU). To better manage the explosive increment of low risk suspicious transactions reporting from financial institutions and to conjugate data converged into the KoFIU from various organizations, the adoption of a knowledge-based system is definitely required. We designed and constructed the knowledge-based system for anti-money laundering by committing experts of each specific financial industry co-worked with a knowledge engineer. The outcome of the knowledge base implementation shows that the knowledge-based system is filtering STRs in the primary analysis step efficiently and so has made great contribution to improve efficiency and effectiveness of the analysis process. It can be said that establishing the foundation of the knowledge base under the entire framework of the knowledge-based system for consideration of knowledge creation and management is indeed valuable.

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Self-Organizing Fuzzy Systems with Rule Pruning (규칙 제거 기능이 있는 자기구성 퍼지 시스템)

  • Lee, Chang-Wook;Lee, Pyeong-Gi
    • Journal of the Korean Society of Industry Convergence
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    • v.6 no.1
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    • pp.37-42
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    • 2003
  • In this paper a self-organizing fuzzy system with rule pruning is proposed. A conventional self-organizing fuzzy system having only rule generation has a drawback in generating many slightly different rules from the existing rules which results in increased computation time and slowly learning. The proposed self-organizing fuzzy system generates fuzzy rules based on input-output data and prunes redundant rules which are caused by parameter training. The proposed system has a simple structure but performs almost equivalent function to the conventional self-organizing fuzzy system. Also, this system has better learning speed than the conventional system. Simulation results on several numerical examples demonstrate the performance of the proposed system.

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Intelligent Ship s Steering Gear Control System Using Linguistic Instruction (언어지시에 의한 지능형 조타기 제어 시스템)

  • Park, Gyei-Kark;Seo, Ki-Yeol
    • Journal of the Korean Institute of Intelligent Systems
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    • v.12 no.5
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    • pp.417-423
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    • 2002
  • In this paper, we propose intelligent steering control system that apply LIBL(Linguistic Instruction Based Learning) method to steering system of ship and take the place of process that linguistic instruction such as officer s steering instruction is achieved via ableman. We embody ableman s suitable steering manufacturing model using fuzzy inference rule by specific method of study, and apply LIBL method to present suitable meaning element and evaluation rule to steering system of ship, embody intelligent steering gear control system that respond more efficiently on officer s linguistic instruction. We presented evaluation rule to constructed steering manufacturing model based on ableman s experience, and propose rudder angle for steering system, compass bearing arrival time, meaning element of stationary state, and correct ableman manufacturing model rule using fuzzy inference. Also, we apply LIBL method to ship control simulator and confirmed the effectiveness.