• Asia pacific journal of information systems
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• 제11권4호
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• pp.99-111
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• 2001

The prediction of stock price index is a very difficult problem because of the complexity of stock market data. It has been studied by a number of researchers since they strongly affect other economic and financial parameters. The movement of stock price index has a series of change points due to the strategies of institutional investors. This study presents a two-stage forecasting model of stock price index using change-point detection and artificial neural networks. The basic concept of this proposed model is to obtain intervals divided by change points, to identify them as change-point groups, and to use them in stock price index forecasting. First, the proposed model tries to detect successive change points in stock price index. Then, the model forecasts the change-point group with the backpropagation neural network(BPN). Finally, the model forecasts the output with BPN. This study then examines the predictability of the integrated neural network model for stock price index forecasting using change-point detection.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2000년도 추계정기학술대회:지능형기술과 CRM
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• pp.427-436
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• 2000

The prediction of stock price index is a very difficult problem because of the complexity of the stock market data it data. It has been studied by a number of researchers since they strong1y affect other economic and financial parameters. The movement of stock price index has a series of change points due to the strategies of institutional investors. This study presents a two-stage forecasting model of stock price index using change-point detection and artificial neural networks. The basic concept of this proposed model is to obtain Intervals divided by change points, to identify them as change-point groups, and to use them in stock price index forecasting. First, the proposed model tries to detect successive change points in stock price index. Then, the model forecasts the change-point group with the backpropagation neural network (BPN). Fina1ly, the model forecasts the output with BPN. This study then examines the predictability of the integrated neural network model for stock price index forecasting using change-point detection.

• 대한수학회지
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• 제45권6호
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• pp.1725-1740
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• 2008

In this paper, we introduce a fixed point index of weakly inward 1-set-contraction mappings. With the aid of the new index, we obtain some new fixed point theorems, nonzero fixed point theorems and multiple positive fixed points for this class of mappings. As an application of nonzero fixed point theorems, we discuss an eigenvalue problem.

• Communications for Statistical Applications and Methods
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• 제8권2호
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• pp.543-556
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• 2001

This study suggests integrated neural network modes for he stock price index forecasting using change-point detection. The basic concept of this proposed model is to obtain significant intervals occurred by change points, identify them as change-point groups, and reflect them in stock price index forecasting. The model is composed of three phases. The first phase is to detect successive structural changes in stock price index dataset. The second phase is to forecast change-point group with various data mining classifiers. The final phase is to forecast the stock price index with backpropagation neural networks. The proposed model is applied to the stock price index forecasting. This study then examines the predictability of integrated neural network models and compares the performance of data mining classifiers.

• 대한정형도수물리치료학회지
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• 제8권1호
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• pp.31-48
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• 2002

This study is aimed to find out and define how the muscular-skeletal pain of the Aged, according to their residential circumstance, sex and age, can affect the subjective health index and how all these are related and associated with. For the period of June 1 to July 31, 2001, in order to study and define how the muscular-skeletal pain are related to the subjective health index of the Aged, we have conducted an enquete through a direct interview with 693 persons over age sixty-five (65) in Daejon and in other adjacent areas, divided into three different residential types "The Aged living at home", "The Aged living at welfare facilities" and "The Aged living alone". The study concludes followings : 1. Generally, muscular-skeletal pain and the subjective health index of the Aged, are a lot influenced by and related to their residential circumstance, their sex and their age. 2. With regard to the muscular-skeletal pain of the Aged by their sex, it was analyzed that, on an average, the female-Aged gains 3.0 point and the female-Aged suffers from this pain more severely. In analyzing this pain by their residential type, it was found that, on an average, the 3.0 point goes for "the Aged living alone", which explains the Aged living alone is having the most serious pain. 3. With regard to the subjective heath index of the all Aged participated in this research, the analysis indicates 8.8 point and this is considered as a general standard (7-10 point). In analyzing this index by their sex, the female-Aged gains 8.6 point only and it explains a lot of female-Aged consider they are not really healthy. In analyzing this index by their residential type, "the Aged living at welfare facilities" and "the Aged living alone" gain the comparatively lower point, - respectively 8.4 point for the Aged living at welfare facilities and 8.8 point for the Aged living alone. The Aged of these two residential types express they are obviously in a bad condition of health, which makes us think a lot.

• 터널과지하공간
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• 제5권2호
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• pp.144-154
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• 1995

In this paper, we make a study on comparison and evaluation of the seoul granite properties, which are unit weight, uniaxial compressive strength, Brazilian tensile strength and, point load strength. The typical result are as follow- 1. From the measured value of point load strength anisotropy index, the seoul granite is considered to be homogeneous. 2. There is a linear relationship between uniaxial compressive strength and size corrected point load strength index. 3. Brazilian tensile strength and size corrected point load strength index are closely tied together.

• Communications for Statistical Applications and Methods
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• 제10권1호
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• pp.153-166
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• 2003

This study presents the time-divided forecasting model to integrate evolutionary optimization algorithm and change point detection based on artificial neural networks (ANN) for the prediction of (Korea) stock price index. The genetic algorithm(GA) is introduced as an evolutionary optimization method in this study. The basic concept of the proposed model is to obtain intervals divided by change points, to identify them as optimal or near-optimal change point groups, and to use them in the forecasting of the stock price index. The proposed model consists of three phases. The first phase detects successive change points. The second phase detects the change-point groups with the GA. Finally, the third phase forecasts the output with ANN using the GA. This study examines the predictability of the proposed model for the prediction of stock price index.

• Spatial Information Research
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• 제16권2호
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• pp.237-247
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• 2008

지도좌표를 가진 정보의 통계적 분석은 GIS 중요기능 중 하나로 인정되고 있다. 그 중 가장 기본적인 분석의 하나로 점사상에 대한 밀도분석이 이루어지고 있다. 밀도분석은 일반적으로 라스터 분석의 일부로 간주되고 있으며, 적합한 밀도분석을 위해서는 kernel 반경으로 알려진 검색반경의 결정이 중요한 것으로 알려져 있다. 본 연구에서는 기존 연구 결과에서 검색반경 설정에 유용한 것으로 알려진 L-지표를 이용하여, 비즈니스 GIS 분야에 축적된 점사상의 밀도 분석에 적합한 반경을 추정하고, 추정된 결과를 기반으로 점사상의 특성에 따른 L-지표의 거동을 고찰하였다. 연구결과 점사상이 대상지역의 일부 지역에서 크게 밀집되는 경우에는 L-지표가 대상지역의 크기와 무관하게 일정한 반경에서 극대값을 보이기 때문에 L-지표를 이용하여 검색반경을 설정하는 것이 유용함을 알 수 있었다. 반면, 점사상이 대상지역에 고루 분포하는 경우에는 L-지표의 극대값이 나타나는 반경이 대상지역의 크기에 따라 영향을 받기 때문에 L-지표를 이용하여 검색반경을 설정하는 것이 적합하지 않음을 알 수 있었다. 따라서 L-지표를 이용한 점사상 밀도의 검색반경 설정에는 점사상의 분포특성이 고려되어야 함을 알 수 있었다.

• 대한전기학회논문지
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• 제45권1호
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• pp.146-158
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• 1996

The WKB method has been widely used in evaluating of the propagation characteristics of planar waveguides with graded-index profiles. This method, however, yields large errors when a turning point is near or at the discontinuity in the presence of the index discontinuity or index slope discontinuity. Especially, in the case of a truncated-index profile, this phenomenon appears more clearly in the low-order modes and near the cutoff regions. The MWKB method is introduced to reduce these inherent errors of the conventional WKB method. The MWKB method is based on both the linearization of the index profile from an index discontinuity and the introduction of a virtual turning point. It is noticed that the b-v curves obtained by the MWKB method agree well with those of the finite-difference method, and that the phase shift at a turning point depends on both the index profile and its propagation constant. (author). refs., figs.

• Journal of Information Processing Systems
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• 제16권3호
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• pp.688-698
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• 2020

Point clouds have ability to express the spatial entities, however, the point clouds redundancy always involves some uncertainties in computer recognition and model construction. Therefore, point clouds thinning is an indispensable step in point clouds model reconstruction and other applications. To overcome the shortcomings of complex classification index and long time consuming in existing point clouds thinning algorithms, this paper proposes a point clouds fast thinning algorithm. Specifically, the two-dimensional index is established in plane linear array (x, y) for the scanned point clouds, and the thresholds of adjacent point distance difference and height difference are employed to further delete or retain the selected sample point. Sequentially, the index of sample point is traversed forwardly and backwardly until the process of point clouds thinning is completed. The results suggest that the proposed new algorithm can be applied to different targets when the thresholds are built in advance. Besides, the new method also performs superiority in time consuming, modelling accuracy and feature retention by comparing with octree thinning algorithm.