• 대한전기학회논문지
• /
• 제37권10호
• /
• pp.727-732
• /
• 1988

In this paper, a parameter estimation method of linear systems with bounded output disturbances is studied. The bound of the disturbances is assumed to known Weighting factors are proposed to modify LS(Least Square) algorithm in the parameter estimation method. The conditions of weighting factors are given so that the estimation method has good convergence properties. This condition is more relaxed form than other known conditions. The compensation term in the estimation equations is represented by a function of the output prediction error and this function should lie in a specified region on x-y plane to satisfy these conditions of weighting factors. A set of weighting factor is selected and an algorithm is proposed using this set of weighting factor. The proposed algorithm is compared with another existing algorithm by simulation and its performance in parameter estimation id discussed.

• 제어로봇시스템학회논문지
• /
• 제12권7호
• /
• pp.631-636
• /
• 2006

In this paper, an algorithm of time series function forecasting using GMDH(group method of data handling) algorithm that gives more weight to the recent data is proposed. Traditional methods of GMDH forecasting gives same weights to the old and recent data, but by the point of view that the recent data is more important than the old data to forecast the future, an algorithm that makes the recent data contribute more to training is proposed for more accurate forecasting. The average error rate of electric power demand forecasting by the traditional GMDH algorithm which does not use data weighting algorithm is 0.9862 %, but as the result of applying the data weighting GMDH algorithm proposed in this paper to electric power forecasting demand the average error rate by the algorithm which uses data weighting algorithm and chooses the best data weighting rate is 0.688 %. Accordingly in forecasting the electric power demand by GMDH the proposed method can acquire the reduced error rate of 30.2 % compared to the traditional method.

• 대한산업공학회지
• /
• 제26권1호
• /
• pp.27-35
• /
• 2000

For a weighting method to be practically valid, it should produce weights which coincide with the relative importance of attributes perceived by the decision maker. In this paper, 'bootstrapping' is used to compare the practical validities of five weighting methods frequently used; the rank order centroid method, the rank reciprocal method, the rank sum method, the entropic method, and the geometric mean method. Bootstrapping refers to the procedure where the analysts allow the decision maker to make careful judgements on a series of similar cases, then infer statistically what weights he was implicitly using to arrive at the particular ranking. The weights produced by bootstrapping can therefore be regarded as well reflecting the decision maker's perceived relative importances. Bootstrapping and the five weighting methods were applied to a job selection problem. The results showed that both the rank order centroid method and the rank reciprocal method had higher level of practical validity than the other three methods, though a large difference could not be found either in the resulting weights or in the corresponding solutions.

• Journal of applied mathematics & informatics
• /
• 제30권3_4호
• /
• pp.593-602
• /
• 2012

In this paper, we first introduce a special type of multisplitting method with different weighting scheme, and then we provide convergence results of multisplitting methods with different weighting schemes corresponding to both the AOR-like multisplitting and the SSOR-like multisplitting.

• 한국정보통신학회논문지
• /
• 제16권3호
• /
• pp.533-540
• /
• 2012

본 논문은 의사연관피드백과 의미특징기반의 용어 가중치에 의한 문서요약 방법을 제안한다. 제안된 방법은 의사연관피드백을 이용하여 사용자의 간섭을 최소화 시키며, 의미특징으로부터 유도된 용어의 가중치는 문장집합의 내부 특징을 잘 나타나기 때문에 문서요약의 질을 향상할 수 있다. 또한 가중치가 부여된 의미특징과 확장된 질의를 이용하여서 사용자의 요구사항과 제안방법의 요약결과 사이의 의미적 차이를 감소시킨다. 실험결과 제안방법이 용어의 가중치를 부여하지 않은 방법에 비해서 좋은 성능을 보인다.

• 한국지능정보시스템학회:학술대회논문집
• /
• 한국지능정보시스템학회 1999년도 추계학술대회-지능형 정보기술과 미래조직 Information Technology and Future Organization
• /
• pp.323-335
• /
• 1999

In this paper, we propose a new hybrid model of artificial neural networks(ANNs) and genetic algorithm (GA) to optimal feature transformation and feature weighting. Previous research proposed several variants of hybrid ANNs and GA models including feature weighting, feature subset selection and network structure optimization. Among the vast majority of these studies, however, ANNs did not learn the patterns of data well, because they employed GA for simple use. In this study, we incorporate GA in a simultaneous manner to improve the learning and generalization ability of ANNs. In this study, GA plays role to optimize feature weighting and feature transformation simultaneously. Globally optimized feature weighting overcome the well-known limitations of gradient descent algorithm and globally optimized feature transformation also reduce the dimensionality of the feature space and eliminate irrelevant factors in modeling ANNs. By this procedure, we can improve the performance and enhance the generalisability of ANNs.

• 환경영향평가
• /
• 제10권1호
• /
• pp.59-71
• /
• 2001

This study aims to propose a determinant model to select a method on calculating weight of each indicator for environmental evaluation. According to analyzing and comparing with three types of methods for calculating weights which are usually used to evaluate environment with indicators, the weights which were obtained by each type were all different from each other. This means that a differential weighting method must be applied to each of environmental evaluation studies. Therefore, a determinant model is required to determine weight-calculating methods. Three types of weighting methods, such as weighting by importance degree, weighting by eigen-value and weighting by analytic hierarchy process, were compared. Under the necessity, a determinant model was drawn for selecting a compatible method to calculate weights of indicators in environmental evaluation.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1999년도 제14차 학술회의논문집
• /
• pp.266-269
• /
• 1999

An electronically Scannable microphone system is in the Planning stage. For this Purpose, a multiple microphone array with controllable delay is available. To achieve effective point-listening characteristics, we proposed an enclosed microphone array system with a complex weighting method. In this system, both the microphone arrangement and the value of the complex weighting are important. In this report, the construction of microphone array system and the signal-processing method are explained, and the calculation method for optimal complex weighting is also presented. A prototype experimental setup is designed and fabricated to verify the expected characteristics.

• Journal of Information Technology Applications and Management
• /
• 제13권1호
• /
• pp.77-94
• /
• 2006

Case-based Reasoning (CBR) is widely used in business and industry prediction. It is suitable to solve complex and unstructured business problems. Recently, the prediction accuracy of CBR has been enhanced by not only various machine learning algorithms such as genetic algorithms, relative weighting of Artificial Neural Network (ANN) input variable but also data mining technique such as feature selection, feature weighting, feature transformation, and instance selection As a result, CBR is even more widely used today in business area. In this study, we investigated the usefulness of the CBR method in forecasting success in implementing ERP systems. We used a CBR method based on the feature weighting technique to compare the performance of three different models : MDA (Multiple Discriminant Analysis), GECBR (GEneral CBR), FWCBR (CBR with Feature Weighting supported by Analytic Hierarchy Process). The study suggests that the FWCBR approach is a promising method for forecasting of successful ERP implementation in Small and Medium sized Enterprises.

• 유체기계공업학회:학술대회논문집
• /
• 유체기계공업학회 2005년도 연구개발 발표회 논문집
• /
• pp.287-294
• /
• 2005

Flow rate measurement uncertainties of the ultrasonic flow meter are generally influenced by many different factors, such as Reynolds number, flow distortion, turbulence intensity, wall surface roughness, velocity integration method along the acoustic paths, and transducer installation method, etc. Of these influencing factors, one of the most important uncertainties comes from the velocity integration method. In the present study, a optimization weighting factor method for 5-chord, which is given by a function of the chord locations of acoustic paths, is employed to obtain the mean velocity in the flow through a pipe. The power law profile is assumed to model the axi-symmetric pipe flow and its results are compared with the present weighting factor concept. For an asymmetric pipe flow, the Salami flow model is applied to obtain the velocity profiles. These theoretical methods are also compared with the previous Gaussian, Chebyshev, and Tailor methods. The results obtained show that for the fully developed turbulent pipe flows with surface roughness effects, the present weighting factor method is much less sensitive than Chebyshev and Tailor methods, leading to a better reliability in flow rate measurement using the ultrasonic flow meters.