• 대한원격탐사학회지
• /
• 제3권2호
• /
• pp.115-119
• /
• 1987

After the introduction of the topologically structured geographic information system(GIS) with relational DBMS, the attribute data can be handled without considering locational data. By utilzing of the characteristic of the relational DBMS, it can be used as an expert system building tool in GIS. The relational DBMS of the GIS furnishes the data needed to perform deductive functions of the expert system, and the rule based approach provides the decision rules. Therefore, rule based approach with the expert judgement can be easily combined with relational DBMS.

• 제어로봇시스템학회논문지
• /
• 제11권2호
• /
• pp.127-136
• /
• 2005

In this paper, a new architecture and comprehensive design methodology of genetically optimized Rule-based Fuzzy Polynomial Neural Networks(gRFPNN) are introduced and a series of numeric experiments are carried out. The architecture of the resulting gRFPNN results from asynergistic usage of the hybrid system generated by combining rule-based Fuzzy Neural Networks(FNN) with polynomial neural networks (PNN). FNN contributes to the formation of the premise part of the overall rule-based structure of the gRFPNN. The consequence part of the gRFPNN is designed using PNNs. At the premise part of the gRFPNN, FNN exploits fuzzy set based approach designed by using space partitioning in terms of individual variables and comes in two fuzzy inference forms: simplified and linear. As the consequence part of the gRFPNN, the development of the genetically optimized PNN dwells on two general optimization mechanism: the structural optimization is realized via GAs whereas in case of the parametric optimization we proceed with a standard least square method-based learning. To evaluate the performance of the gRFPNN, the models are experimented with the use of several representative numerical examples. A comparative analysis shows that the proposed gRFPNN are models with higher accuracy as well as more superb predictive capability than other intelligent models presented previously.

• 한국BIM학회 논문집
• /
• 제12권3호
• /
• pp.30-38
• /
• 2022

Railway is compsed in various components, such as subgrade, track bed, sleeper, rail, and overhead line, on a linear space. Therefore, comprehensive work for various design standards and guidelines is required when designing a railway facility. For this reason, much time and effort are required to review the relevant design standards and guidelines. While, automatic legal check system for BIM models has been developed in the architectural engineering, it has not been developed in the railway engineering. This study reviews the korean design standard and the korean code for railway engineering, and suggests some rule items of logical information. Comparing the suggested rule items to the railway BIM library, items of logical information and additional attribute information are obtained. The analysis results of railway design standards and BIM library presented in this study would be utilized for defining rule-set items that is essential for development of the automatic legal check system for railway BIM models.

• 건축역사연구
• /
• 제23권4호
• /
• pp.69-80
• /
• 2014

The purpose of this paper is to examine the dissolution process of Dongnae-bu Dongheon Block(東萊府 東軒 一廓) under the Rule of Japanese. The results of this study are summarized as follows. First, the space orgnization of Dongnae-bu Dongheon Block(東萊府 東軒 一廓) proved to be clear on the basis of Dongnae-bu Eupji(東萊府 邑誌), the ficture of Dongnae-bu(東萊府) and the Original Land Registration Map(地籍原圖) at the end of Joseon Dynasty. Second, the old government offices, as well as Chungsin-dang(忠信堂), were converted into the local government office for the sake of Japanese colonialism. Third, the old government office and its land were transferred to the banking system(金融組合) and the educational foundation(學校組合) in the interests of Japanese colonist. Finally, the transfer land of civilian industry association forced Mangmi-ru(望美樓) and Dokjin-daeamun(獨鎭大衙門) to remove to another site and the private lots-subdivision assisted space taking to pieces.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2003년도 ICCAS
• /
• pp.1517-1520
• /
• 2003

Generally, the environment we want to apply classifier system to is composed of several state spaces. So in this paper, we propose the layered classifier system having multifarious rule bases. From sensor's inputs, the lower layer of the layered classifier system learns strategies for each environmental state space. The higher layer learns how to allot each rule base of the strategy for environmental state space properly. To evaluate the proposed architecture of classifier system, we designed virtual environment having multifarious state spaces and from the analysis of the experimental results, we affirm that layered classifier system could find better strategies during a little time than other established classifier system's findings.

• 한국자동차공학회논문집
• /
• 제7권7호
• /
• pp.195-201
• /
• 1999

In Rollover crashes, the development of bus structure to ensure the maintenance of survival space for passengers is very important . So, this paper focuses on understanding the possibility of efficient structural development considering rollover strength through computer simulation using the commercial code, LS-DYNA3D at the initial stage of vehicle development structural members, and impact boundary conditions required by ADR59(Australian Design Rule 59)were applied. In order to confirm the validity of the computational results, the test results. After the usefulness of this method of analysis was confirmed , we have proposed the effective modificationfor rollover strength.

• International journal of advanced smart convergence
• /
• 제1권2호
• /
• pp.30-33
• /
• 2012

This paper propose a new design of fuzzy neural networks based on hard partition to generate the rules of the networks. For this we use hard c-means (HCM) clustering algorithm. The premise part of the rules of the proposed networks is realized with the aid of the hard partition of input space generated by HCM clustering algorithm. The consequence part of the rule is represented by polynomial functions. And the coefficients of the polynomial functions are learned by BP algorithm. The number of the hard partition of input space equals the number of clusters and the individual partitioned spaces indicate the rules of the networks. Due to these characteristics, we may alleviate the problem of the curse of dimensionality. The proposed networks are evaluated with the use of numerical experimentation.

• 대한전기학회논문지
• /
• 제33권10호
• /
• pp.381-386
• /
• 1984

This paper deals with the microcomputer realization of EMG pattern recognition system which provides identification of motion commands from the EMG signals for the on-line control of a prosthetic arm. A probabilistic model of pattern is formulated in the feature space of integral absolute value(IAV) to describe the relation between a motion command and the location of corresponding pattern. This model enables the derivation of sample density function of a command in the feature space of IAV. Classification is caried out through the multiclass sequential decision process, where the decision rule and the stopping rule of the process are designed by using the simple mathematical formulas defined as the likelihood probability and the decision measure, respectively. Some floating point algorithms such as addition, multiplication, division, square root and exponential function are developed for calculating the probability density functions and the decision measure. Only six primitive motions and one no motion are incorporated in this paper.

• Communications for Statistical Applications and Methods
• /
• 제10권1호
• /
• pp.203-210
• /
• 2003

In a standard Metropolis-type Monte Carlo simulation, the proposal distribution cannot be easily adapted to "local dynamics" of the target distribution. To overcome some of these difficulties, Duane et al. (1987) introduced the method of hybrid Monte Carlo(HMC) which combines the basic idea of molecular dynamics and the Metropolis acceptance-rejection rule to produce Monte Carlo samples from a given target distribution. In this paper, using the HMC within Gibbs sampler, an asymptotical estimate of the smoothing mean and a general solution to state space modeling in Bayesian framework is obtaineds obtained.

• 디지털콘텐츠학회 논문지
• /
• 제2권2호
• /
• pp.103-115
• /
• 2001

본 논문은 퍼지지식베이스에서 러프 집합과 요인공간이론을 적용하여 최소 결정규칙 생성과 근사추론 연산을 수행하는 두 개의 알고리듬을 제안한다. 최소 결정규칙의 생성은 속성요인에 관련한 상관분석과 베이지안 정리를 응용한 데이터의 분류기법과 리덕트에 의해 수행된다. 이 결정규칙으로 이루어진 최소지식 베이스의 탐색공간에서 소속함수와 t-norm의 합성 연산을 정의한 근사추론 방식에 의해 특정 객체를 검색한다. 본 연구의 러프와 퍼지연산 모듈을 수행하는 제안 알고리듬 기법을 객체및 속성수를 증가시키는 시뮬레이션을 통해 다른 검색이론 및 합성연산 방식과 비교하였다. 그 결과 다른 제 방법보다 본 연구에서 제안하는 기법이 특정 객체를 추출하기 위한 검색연산 시간에 있어 보다 빠르게 검색됨을 입증하였다.