• 한국컴퓨터정보학회논문지
• /
• 제10권1호
• /
• pp.209-216
• /
• 2005

수행 평가는 평가자에 의한 평가 오류 가능성, 채점의 공정성과 신뢰도, 타당도 문제, 채점 기준의 모호성, 객관성 확보에 대한 어려움 등의 문제가 야기되고 있다 이런한 수행 평가의 문제점을 해결하고 교사와 학생의 수행 평가 결과에 대한 만족도를 높이기 위하여, 본 논문에서는 회계 원리 과목을 대상으로 수행 평가의 각 영역에서 영향을 미치는 요인을 분석하여 퍼지 소속 함수를 설계하고 퍼지 규칙을 정의하여 추론을 적용하여 객관적이고 신뢰성이 높은 수행 평가 방법을 제안하였다 또한 제안된 수행 평가 방법에서 수행 평가 항목은 형성 평가와 과제 평가로 구분하여 소속 함수를 설계하였다. 제안된 퍼지 수행 평가 시스템을 통해 산출된 수행 평가 결과는 평정자의 채점 오류에 대한 부담을 줄일 수 있으며 학생들에 게는 정확한 기준과 일관성 있는 채점을 통해 공평하고 신뢰성 있는 평가 결과를 제공한다.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제6권1호
• /
• pp.21-26
• /
• 2006

In this paper, we propose a customer personalized system that presents the web pages to users which are customized to their individuality. It analyzes the action of users who visit the shopping mall, and preferentially supplies the necessary information to them. When they actually buy some items, it forecasts the user's access pattern to web site and their following purchasable items and improves their web page on the bases of their individuality. It reasons the relation among the web documents and among the items by using the log data of web server and the purchase information of DB. For reasoning, it employs Apriori algorithm, which is a method that searches the association rule. It reasons the web pages by considering the user's access pattern and time by using the web log and reasons the user's purchase pattern by using the purchase information of DB. On the basis of the relation among them, it appends the related web pages to link of user's web pages and displays the inferred goods on user's web pages.

• 한국정보처리학회논문지
• /
• 제7권5S호
• /
• pp.1649-1656
• /
• 2000

현재 대다숭의 전자 상거래 시스쳄은 수요자 및 공급자에 많은 부하를 주고 있다. 본 논문은 이러한 문제점을 해결하기 위하여 사례 기반의 추론을 이용한 판매 지원 에이전트를 제안한다. 먼저, 본 논문은 상품 정보 수집 에이전트, 색인 구성 에이전트, 판매 지원 에이전트, 검색엔진 등으로 구성된 다중 에이전트 시스템의 설계 방안을 제안하고 판매 지원 에이전트가 사용자의 취향을 알아내고 이를 흥정과정에 적용할 수 있도록 사례 기반의 지능형 에이전트를 설계한다. 또한, 프로토타입을 구현하여 판매지원 에이전트가 사례기반 추론 방법의 학습을 통하여 고객의 나이, 직업, 학력, 드에 따라 고객의 취향에 맞는상품 정보만을 빠르게 검색하는 과정을 보인다.

• 한국정보시스템학회지:정보시스템연구
• /
• 제8권1호
• /
• pp.27-44
• /
• 1999

Case-Based Reasoning(CBR) offers a new approach for developing knowledge based systems. CBR has several research issues which can be divided into two categories : (1) static issues and (2) dynamic issues. The static issues are related to case representation scheme and case data model, that is, focus on casebase which is a repository of cases. The dynamic issues, on the other hand, are related to case retrieval procedure and problem solving process, i.e. case adaptation phase. This research is forcused on retrieval procedure Traditional query processing accepts precisely specified queries and only provides exact answers, thus requiring users to fully understand the problem domain and the casebase schema, but returning limited or even null information if the exact answer is not available. To remedy such a restriction, extending the classical notion of query answering to approximate query answering(AQA) has been explored. AQA can be achieved by neighborhood query answering or associative query answering. In this paper, neighborhood query answering technique is used for AQA. To reinforce the CBR process, a new retrieval procedure(cooperative CBR) using neighborhood query answering is proposed. An neighborhood query answering relaxes a query scope to enlarge the search range, or relaxes an answer scope to include additional information. Computer Aided Process Planning(CAPP) is selected as cooperative CBR application domain for test. CAPP is an essential key for achieving CIM. It is the bridge between CAD and CAM and translates the design information into manufacturing instructions. As a result of the test, it is approved that the problem solving ability of cooperative CBR is improved by relaxation technique.

• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 1998년도 추계학술대회 학술발표 논문집
• /
• pp.532-538
• /
• 1998

In this paper, a new adaptive fuzzy inference method using neural network based fuzzy reasoning is proposed to make a fuzzy logic control system more adaptive and more effective. In most cases, the design of a fuzzy inference system rely on the method in which an expert or a skilled human operator would operate in that special domain. However, if he has not expert knowledge for any nonlinear environment, it is difficult to control in order to optimize. Thus, using the proposed adaptive structure for the fuzzy reasoning system can controled more adaptive and more effective in nonlinear environment for changing input membership functions and output membership functions. The proposed fuzzy inference algorithm is called adaptive neuro-fuzzy control(ANFC). ANFC can adapt a proper membership function for nonlinear plant, based upon a minimum number of rules and an initial approximate membership function. Nonlinear function approximation and rotary inverted pendulum control system ar employed to demonstrate the viability of the proposed ANFC.

• 한국IT서비스학회지
• /
• 제9권3호
• /
• pp.123-144
• /
• 2010

As knowledge becomes a critical success factor of companies nowadays, lots of rule-based systems have been and are being developed to support their activities. Large number of rule-based systems serve as Web sites to advise, or recommend their customers. They usually use a backward chaining inference algorithm based on backtrack to implement those interactive Web-enabled rule-based systems. However, when the users like customers are using these systems interactively, it happens frequently where the users do not know some of the answers for the questions from the rule-based systems. We are going to design a backward chaining inference methodology considering unknown facts based on backtrack technique. Firstly, we review exact and inexact reasoning. After that, we develop a backward chaining inference algorithm for exact reasoning based on backtrack, and then, extend the algorithm so that it can consider unknown facts and reduce its search space. The algorithm speeded-up inference and decreased interaction time with users by eliminating unnecessary questions and answers. We expect that the Web-enabled rule-based systems implemented by our methodology would improve users' satisfaction and make companies' competitiveness.

• 한국과학교육학회지
• /
• 제26권5호
• /
• pp.620-636
• /
• 2006

The purpose of this study was to analyze one science teacher's understanding of student argumentation and his explicit teaching strategies for implementing it in the classroom. One middle school science teacher, Mr. Field, and his students of 54 participated in this study. Data were collected through three semi-structured interviews, 60 hours of classroom observations, and two times of students' lab reports for eight weeks. Coding categories were developed describing the teacher's understanding of scientific argumentation and a description of the main teaching strategy, the Claim-Evidence Approach, was introduced. Toulmin's approach was employed to analyze student discourse as responses to see how much of this discourse was argumentative. The results indicated that Mr. Field defined scientific inquiry as the abilities of procedural skills through experimentation and of reasoning skills through argumentation. The Claim-Evidence Approach provided students with opportunities to develop their own claims based on their readings, design the investigation for evidence, and differentiate pieces of evidence from data to support their claims and refute others. During this approach, the teacher's role of scaffolding was critical to shift students' less extensive argumentation to more extensive argumentation through his prompts and questions. The different level of teacher's involvement, his explicit teaching strategy, and the students' scientific knowledge influenced the students' ability to develop and improve argumentation.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
• /
• pp.860-863
• /
• 1997

FCM(Fuzzy Cognitive Map) is a fuzzy signed directed graph for representing causal reasoning which has fuzziness between causal concepts. Authors have already proposed FCM-based fault diagnostic scheme. However, the previously proposed scheme has the problem of lower diagnostic resolution. In order to improve the diagnostic resolution, a new diagnostic scheme based on extended FCM which incorporates the concept of fuzzy number into FCM is developed in this paper. Furthermore, an enhanced TAM(Temporal Associative Memory) recall procedure and pattern matching scheme are also proposed.

• 전력전자학회:학술대회논문집
• /
• 전력전자학회 2001년도 Proceedings ICPE 01 2001 International Conference on Power Electronics
• /
• pp.380-383
• /
• 2001

The paper presents a cost effective and increased performance position servo system using the TMS320F240 digital signal processor (DSP) produced by Texas Instruments as microprocessor and Brushless Direct Current Motor (BLDCM) as executor. In order to make up for the drawback of conventional PID controls, the fuzzy PID is employed. The result of simulations and experiments has confirmed that the whole system is simple and reliable; the robustness of system is improved by using fuzzy PID.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2001년도 ICCAS
• /
• pp.146.2-146
• /
• 2001

Recently, a need of non-industrial robot, such as service, medical, entertainment and house-keeping robot, has been increased. Therefore, the capability of robot which can do intelligent behavior like interaction with men and its environment become more prominent than the capability of executing simple repetitive task. To implement an intelligent robot which provides intelligent behavior, an effective system architecture including perception, learning, reasoning and action part is necessary. Control architectures for intelligent robot can be divided into two different classes. One is deliberative type controller which is applicate to high level intelligence like environment ...