• Journal of Power System Engineering
• /
• v.10 no.4
• /
• pp.159-164
• /
• 2006

In recent, the marine engine of a large size is being realized a lower speed, longer stroke and a small number of cylinders for the energy saving. Consequently the variation of rotational torque became larger than former days because of the longer delay-time in fuel oil injection process and an increased output per cylinder. It was necessary that algorithms have enough robustness to suppress the variation of the delay-time and the parameter perturbation. This paper shows the structure of hybrid F-NFC against the delay-time and the perturbation of engine parameter as modeling uncertainties, and the design of the robust speed controller by hybrid F-NFC for the engine. And, The Parameter values of linear equation are determined by RC-GA for F-NFS. The hybrid F-NFC is combined the F-NFC and PID controller for filling up each.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2000.04a
• /
• pp.406-409
• /
• 2000

이 논문에서는 웹 서버에 발생할 수 있는 장애 항목들을 정의하고, 발생한 장애를 자동적으로 진단하고 이를 검출하기 위한 방법을 규칙기반 추론기법을 사용하여 제안하였다. 즉, 웹 서버 관리에서 발생할 수 있는 장애 항목을 정의하고, 장애를 진단하기 위한 규칙을 제안하였는데, 장애 항목으로는 프로세스 장애, 서버 과부하, 인터페이스 장애, 구성 및 성능 장애를 정의하였으며, 각 장애 항목을 진단하기 위한 지식을 활성 네트워크기법을 적용하여 표현하고, 이를 시스템 레벨 장애 진단 생성규칙과 서비스 레벨 장애 진단 생성규칙으로 정형화하였다. 그리고 제안한 장애 진단규칙의 타당성을 증명하기 위한 장애 환경 구성을 구성하고, 각 장애 환경에 대한 생성규칙 적용과정을 실험을 통하여 제시하였다. 이 논문에서는 기하 급수적으로 증가하는 웹 서버의 장애를 관리하기 위한 메커니즘 제안함으로써 웹 서버 관리에 소요되는 관리자의 노력을 최소화할 수 있는 지능적인 장애 관리를 위한 방법론을 제시하고자 한다.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.27 no.4
• /
• pp.69-76
• /
• 2004

A framework for knowledge management system has been explored which enables the semantic search of knowledge on the web. Knowledge representation by RDF and RDF schema enables machine cognition of knowledge documents. Dublin core was adopted for structured metadata representation. Thereby, it enables the CBR and rule based reasoning for intelligent knowledge retrieval. Grafting of the WFMS technique unto the KMS facilitates the effective utilization of process knowledge and creation of new knowledge.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2008.05a
• /
• pp.16-18
• /
• 2008

유비쿼터스 컴퓨팅 환경에서 상황을 인지해 각 사용자에게 필요한 서비스를 자동으로 제공하거나, 사용자로부터 요청받은 서비스를 주어진 환경에서 성공적으로 수행하기 위해서는 그 서비스를 수행하는 각각의 장치들은 일정 수준 이상의 지능을 갖고 있어야 한다. 본 연구에서는 일차 술어 논리를 사용하는 규칙 기반 추론 엔진으로 JRM-S를 개발하였다. 본 엔진은 위치 기반 상황 모델 구축을 위해 공간지식 처리 기능을 갖고 있으며, 유비쿼터스 환경에 존재하는 서비스 장치들에게 상황을 인식할 수 있는 지능을 부여하기 위한 지식 처리기로 사용될 수 있다.

• The Journal of the Korea Contents Association
• /
• v.11 no.4
• /
• pp.74-82
• /
• 2011

To do fuzzy modelling of a nonlinear process needs to analyze the characteristics of input-output of fuzzy inference systems according to the division of entire input spaces and the fuzzy reasoning methods. For this, fuzzy model is expressed by identifying the structure and parameters of the system by means of input variables, fuzzy partition of input spaces, and consequence polynomial functions. In the premise part of the fuzzy rules Min-Max method using the minimum and maximum values of input data set and C-Means clustering algorithm forming input data into the clusters are used for identification of fuzzy model and membership functions are used as a series of triangular, gaussian-like, trapezoid-type membership functions. In the consequence part of the fuzzy rules fuzzy reasoning is conducted by two types of inferences such as simplified and linear inference. The identification of the consequence parameters, namely polynomial coefficients, of each rule are carried out by the standard least square method. And lastly, using gas furnace process which is widely used in nonlinear process we evaluate the performance and the system characteristics.

• Journal of KIISE:Software and Applications
• /
• v.34 no.8
• /
• pp.763-771
• /
• 2007

As software is widely used on various environments today, there is an increasing need for adaptive software. Adaptive software is robust and flexible software that modifies its own behavior in response to the changes in its environment. Due to time constraints, high complexity and so on, it is hard to acquire context information from environment. So, when implementing software, it is common to think easily acquired data to be the environments. This research proposes an adaptive software framework that assumes plane images to be environments. Plane images are easy to acquire and have enough complexity. From this, our framework is able to acquire context information, reasons with action rule, and acts on the result of reasoning. Stand on this framework, implements software that plays a simple game automatically.

• Journal of KIISE
• /
• v.43 no.4
• /
• pp.470-479
• /
• 2016

As the number of various types of media data such as UCC (User Created Contents) increases, research is actively being carried out in many different fields so as to provide meaningful media services. Amidst these studies, a semantic web-based media classification approach has been proposed; however, it encounters some limitations in video classification because of its underlying ontology derived from meta-information such as video tag and title. In this paper, we define recognized objects in a video and activity that is composed of video objects in a shot, and introduce a reasoning approach based on description logic. We define sequential rules for a sequence of shots in a video and describe how to classify it. For processing the large amount of increasing media data, we utilize Spark streaming, and a distributed in-memory big data processing framework, and describe how to classify media data in parallel. To evaluate the efficiency of the proposed approach, we conducted an experiment using a large amount of media ontology extracted from Youtube videos.

• The Transactions of the Korea Information Processing Society
• /
• v.6 no.1
• /
• pp.96-106
• /
• 1999

Case-Base Reasoning(CBR) solves the new problems by reusing the solutions to previously solved problems. But, there are differences between previously known case and a new problems. To solve this problem Case-Based System have to adapt the solution of the case to suit a new situation. In current CBR systems, case adaptation is usually performed by rule-based method that use rules hand-coded by the system developer. So, CBR system designer faces knowledge acquisition bottleneck akin to those found in traditional expert system design. To solve this problem, in this thesis, we present an automatic learning method of case adaptation knowledge using case base, we use a method of comparing cases in the case base to learn adaptation knowledge. The system is tested in the domain for the decision of travel-price. The result shows accuracy improvement in comparison with case retrieval-only system.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.5 no.4
• /
• pp.738-745
• /
• 2001

In this paper, when the moving object move to the three-dimentional space, the tracking system track the moving object using the fuzzy reasoning. The joint angle el of the manipulator rotate from $0^{\circ}\; to\; 360^{\circ}$ , and the joint angle $\theta_2$rotate from$0^{\circ}\; to\; 360^{\circ}$. The fuzzy singleton is used for fuzzification and the control rule is twenty five and the fuzzy inference method is simplified Mamdani's reasoning and the defuzzification is the SCOG(Simplified Center Of Gravity) of the fuzzy controller To measure of the performance of the designed system, the fuzzy controller is compared with the CTM(Computed Torque Method) controller at the same condition. when the disturbance torque is ON, the both of CTM and fuzzy controller tracked object without error, However, the disturbance torque changed 0.4N, the CTM controller is 10 times greater than fuzzy controller at the sum of absolute error difference. The designed system is showed it's robustness against with disturbance.

• Journal of Korean Elementary Science Education
• /
• v.38 no.1
• /
• pp.73-86
• /
• 2019

The purpose of this study is to investigate the characteristics of problem solving strategies that gifted students use in science inquiry problem. The subjects of the study are the notes and presentation materials that the 15 team of elementary and junior high school students have solved the problem. They are a team consisting of 27 elementary gifted and 29 middle gifted children who voluntarily selected topics related to dimple among the various inquiry themes. The analysis data are the observations of the subjects' inquiry process, the notes recorded in the inquiry process, and the results of the presentations. In this process, the knowledge related to dimple is classified into the declarative knowledge level and the process knowledge level, and the strategies used by the gifted students are divided into general strategy and supplementary strategy. The results of this study are as follows. First, as a result of categorizing gifted students into knowledge level, six types of AA, AB, BA, BB, BC, and CB were found among the 9 types of knowledge level. Therefore, gifted students did not have a high declarative knowledge level (AC type) or very low level of procedural knowledge level (CA type). Second, the general strategy that gifted students used to solve the dimple problem was using deductive reasoning, inductive reasoning, finding the rule, solving the problem in reverse, building similar problems, and guessing & reviewing strategies. The supplementary strategies used to solve the dimple problem was finding clues, recording important information, using tables and graphs, making tools, using pictures, and thinking experiment strategies. Third, the higher the knowledge level of gifted students, the more common type of strategies they use. In the case of supplementary strategy, it was not related to each type according to knowledge level. Knowledge-based learning related to problem situations can be helpful in understanding, interpreting, and representing problems. In a new problem situation, more problem solving strategies can be used to solve problems in various ways.