• 철학연구
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• 제139권
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• pp.1-21
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• 2016

문장 서술의 일관성이나 진 위를 신속 정확히 파악하기 위해서 컴퓨터의 힘을 빌릴 수 있다. 따라서 문장논리의 컴퓨터프로세싱으로 문장 전체 서술의 일관성이나 진 위를 신속 정확히 파악하기 위한 연구가 있을 만하다. 이런 필요에 따라 본 연구에서는 컴퓨터프로세싱과정을 기획하고, 그 프로세싱에 필요한 테이블을 작성하고, 그리고 5개 논리규칙의 테이블을 우선 개발하여 활성화해본다. 그래서 차후 연구에서 10개의 기본추론규칙과 11개의 파생추론규칙 각각의 테이블을 개발하고, 그 다음 개발된 테이블들을 활성화하여 구축한 DB 위에 서버 프로그래밍 JSP와 클라이언트 프로그래밍 JAVA를 이용하여 문장논리규칙을 프로세싱하는 토대를 마련한다. 2장에서 프로세싱과정의 기획은 먼저 논리연산테이블을 탐색해서 논리규칙과 추론규칙을 공식으로 구분하고, 공식에 사용할 조합을 구분해서 순번으로 열거하는 작업을 하도록 하여, 변수 테이블, 논리기호 테이블, 입력처리 테이블을 작성한다. 그래서 차후 연구에서 주어부와 술어부를 활성화한 DB 위에 서버 프로그래밍 JSP와 클라이언트 프로그래밍 JAVA를 이용하여 문장의 참 거짓을 판명하도록 준비한다. 3장에서는 2장에서 작성 준비한 테이블을 참고해서 문장논리를 위해 명제적 계산, 문장논리 계산 혹은 진술논리 계산에 사용되는 5개의 논리규칙 즉, 이중부정규칙, 드모르간규칙, 교환규칙, 결합규칙 그리고 분배규칙 모두의 테이블을 개발하고, 마지막 4장에서는 개발한 테이블의 활성화로 DB 구축과 더불어 논리규칙 프로세싱하는 단계까지 이론적 구상을 해본다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.520-523
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• 1997

This paper presents FPGA implementation of fuzzy controller using Product-Sum inference method. Product-Sum inference method has much better performance than other inference methods. This fuzzy controller is composed of several digital modules, e.g. fuzzifier, rule base, adder, multiplier, select center and divider, and is operated by error and error variation. We synthesized the fuzzy controller and performed wave simulation using Xilinx VHDL tool(ViewLogic, ViewSim).

• 디지털콘텐츠학회 논문지
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• 제5권2호
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• pp.128-132
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• 2004

In this paper, a Fuzzy Inference System(FIS) based watermarking algorithm in Discrete Wavelet Transform(DWT) domain is proposed. A 2D fuzzy inference values, in which the inputs are parameters of the coefficients of the DWT block of the original image and the output is strength of watermark embedded, is devised. The fuzzy inference algorithm guarantees that the watermark to be embedded into the original image adaptively. The experimental results shows that proposed approach is robust to the digital image processing schemes.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 G
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• pp.2856-2858
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• 1999

In this paper, the FPNN(Fuzzy Polynomial Neural Networks) algorithm with multi-layer fuzzy inference structure is proposed for the model identification of a complex nonlinear system. The FPNN structure is generated from the mutual combination of PNN (Polynomial Neural Network) structure and fuzzy inference method. The PNN extended from the GMDH(Group Method of Data Handling) uses several types of polynomials such as linear, quadratic and modifled quadratic besides the biquadratic polynomial used in the GMDH. In the fuzzy inference method, simplified and regression polynomial inference method which is based on the consequence of fuzzy rule expressed with a polynomial such as linear, quadratic and modified quadratic equation are used Each node of the FPNN is defined as a fuzzy rule and its structure is a kind of fuzzy-neural networks. Gas furnace data used to evaluate the performance of our proposed model.

• 한국학교수학회논문집
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• 제26권1호
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• pp.21-47
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• 2023

본 연구에서는 문화-역사적 활동이론에 기반하여, 표집 시뮬레이션을 활용한 비형식적 통계적 추리의 교수-학습 과정을 활동체계로 고려하고, 이러한 활동체계에서 발생하는 모순과 모순에 의한 변화를 확인하고자 하였다. 이를 위해 초등학생 5~6학년 20명을 대상으로 표집 시뮬레이션을 활용한 비형식적 통계적 추리에 대한 수업을 진행하고 활동체계를 분석하였다. 주제분석을 수행한 결과는 다음과 같다. 먼저, 규칙과 목표, 인공물과 목표 사이의 모순이 발생했으며, 이를 해결하는 과정에서 경험적 표집 분포의 시각화라는 새로운 인공물이 도입되는 것을 확인할 수 있었다. 또한, 규칙과 인공물, 규칙과 주체 사이의 모순이 발생했으며, 이를 해결하는 과정에서 표본 평균들의 평균을 구하는 알고리즘이 새로운 규칙으로 도입되는 것을 확인할 수 있었다.

• 한국통신학회논문지
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• 제17권5호
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• pp.482-494
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• 1992

In this paper, the neuro-fuzzy inferene system for the effective object recognition is studied. The proposed neuro-fuzzy inference system combines learning capability of neural network with inference process of fuzzy theory, and the system executes the fuzzy inference by neural network automatically. The proposed system consists of the antecedence neural network, the consequent neural network, and the fuzzy operational part, For dissolving the ambiguity of recognition due to input variance in the neuro-fuzzy inference system, the antecedence’s fuzzy proposition of the inference rules are automatically produced by error back propagation learining rule. Therefore, when the fuzzy inference is made, the shape of membership functions os adaptively modified according to the variation. The antecedence neural netwerk constructs a separated MNN(Model Classification Neural Network)and LNN(Line segment Classification Neural Networks)for dissolving the degradation of recognition rate. The antecedence neural network can overcome the limitation of boundary decisoion characteristics of nrural network due to the similarity of extracted features. The increased recognition rate is gained by the consequent neural network which is designed to learn inference rules for the effective system output.

• Journal of the Korean Data and Information Science Society
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• 제18권4호
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• pp.1157-1170
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• 2007

LBS must manage various context data and make the best use of this data for application service in ubiquitous environment. Conventional mobile object data management architecture did not consider process of context data. Therefore a new mobile data management framework is needed to process location context data. In this paper, we design a new context management framework for a location based application service. A suggestion framework is consisted of context collector, context manager, rule base, inference engine, and mobile object context database. It describes a form of rule base and a movement process of inference engine that are based on location based application scenario. It also presents an embodiment instance of interface which suggested framework is applied to location context interference of mobile object.

• 한국정보처리학회논문지
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• 제7권5호
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• pp.1434-1445
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• 2000

An expert system executes the inference, based on the knowledge of specific domain. the reliability on the results of inference depends upon both the consistency and accuracy of knowledge. This is the reason why expert system requires the facilities which can practice an access to the various kinds of knowledge and maintain the consistency and accuracy of knowledge an maintain the consistency and accuracy of knowledge. This paper is to implement an expert system permitting an access of declarative and procedural knowledge in the knowledge base and in the data base. This paper is also to implement a knowledge acquisition system which adds the knowledge a only if its accuracy and consistency are maintained, after verifying the potential errors such as contradiction, redundancy, circulation, non-reachable rule and non-lined rule. In consequence, the expert system realizes a good access to the various sorts of knowledge and increases the reliability on the results of inference. The knowledge acquisition system contributes tro strengthening man-machine interface that enables users to add the knowledge easily to the knowledge base.

• 전기학회논문지P
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• 제54권2호
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• pp.67-72
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• 2005

This paper presents a method to select contingency ranking considering voltage security problems in power systems. Direct method which needs not the detailed knowledge of the post contingency voltage at each bus is used. Based on system operator's experience and knowledge, the membership functions for the MVAR mismatch and allowable voltage violation are justified describing linguistic representation with heuristic rules. Rule base is used for the computation of severity index for each contingency by fuzzy inference. Contingency ranking harmful to the system is formed by the index for security evaluation. Compared with 1P-1Q iteration, this algorithm using direct method and fuzzy inference shows higher computation speed and almost the same accuracy. The proposed method is applied to model system and KEPCO pratical system which consists of 311 buses and 609 lines to show its effectiveness.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1987년도 전기.전자공학 학술대회 논문집(II)
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• pp.1329-1332
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• 1987

This paper describes a design of the expert system for diagnosis of abnormal gait patients. This system makes the rule-based representation that can easily extend the knowledge-base and naturally represent the uncertainty, and the inference engine that uses forward chaining which covers the reasoning from the first condition to the goal. The results of inferring various maladies using this system are as follows: 1) In cases of progressive muscular dystrophy, cerebral vascular accident, peripheral neuropathic lesion and peroneal nerve injury, the result of inference is the same as that of medical specialists' with 100% accuracy. 2) In cases of Neuritis, Paralysis agitan and Brain tumor, the accuracy of inference is less than 50% compared to that of medical specialists. With above results, we decide that the rule-based representations of some maladies ard accurate relatively, but that the correction and the extention of some rules and some methods of problem solving are required in order to construct the complete expert system for diagnosis of abnormal gait patients.