• 대한전기학회논문지
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• 제45권4호
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• pp.602-611
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• 1996

In this paper, radial basis function networks with two hidden layers, which employ the K-means clustering method and the hierarchical training, are proposed for improving the short-term predictability of chaotic time series. Furthermore the recursive training method of radial basis function network using the recursive modified Gram-Schmidt algorithm is proposed for the purpose. In addition, the radial basis function networks trained by the proposed training methods are compared with the X.D. He A Lapedes's model and the radial basis function network by nonrecursive training method. Through this comparison, an improved radial basis function network for predicting chaotic time series is presented. (author). 17 refs., 8 figs., 3 tabs.

• 한국항해학회지
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• 제24권3호
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• pp.147-155
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• 2000

In this paper, we propose the Chaos Fuzzy controller to analyze the chaotic character of time series obtained from the specific plant and to predict the short-term for power consumption of the plant using the Fuzzy controller. We compared the predicted data with the active ones and checked the error generated by them after we time series of supplied power to the proposed controller. As a result of the simulation, we obtained a admirable consequence that the proposed controller can be advanced through various and accurate data acquisition, and continuous analysis of the resident and industrial environment.

• 복식문화연구
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• 제18권6호
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• pp.1274-1290
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• 2010

This study analyzed the design elements and fashion images of women's knitwear in collections of Paris, Milan, London and New York between 2003 and 2008, and examined knitwear trends in an effort to verify whether knitwear trends are repeated in certain cycles, whether they show complicated patterns in cycles and yet occur in quasi cycles, or whether they occur non-periodically in complicated forms of chaotic cycles. Trend cycle analysis results are deemed to identify the time series attribute of knit fashions. It also sought to categorize the attribute of various factors influencing knitwear trends with a view to determining relevancy between design elements, and to present the direction of predicting knitwear fashion trends and the progression of short-term knitwear trends. This study reached the following conclusion. According to design elements or fashion images, knitwear fashion trends occur in cycles, quasi cycles, non-periodical cycles. These cyclic characteristics can be used as scientific data for planning knitwear products. The study confirmed close relevancy between fashion images and fashion elements. It identified close relevancy between designs with similar fashion elements and images through coordinates by year and season, and it is possible to make short-term prediction of trend direction through the flow of coordinates. Time series data were insufficient, thereby making it difficult to perfectly verify chaos indices and giving limitations to this study. A study with more time series data will produce a more effective method of predicting and using knitwear fashion trends.

• 물과 미래
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• 제27권3호
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• pp.45-54
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• 1994

물수지 모델을 사용하여 발생시킨 시계열에 대해서 프랙탈(Fractal) 차원의 기본 이론이 소개 및 적용되었고 물수지 방정식이 넓은 지역에 대해 계절 시간 규모로 분석하였다. 중간 규모 순환의 발생과 변화에 있어 강우의 국부 재순환과 토양 수분의 동력학적 영향이 명시적으로 포함되어 있고 지체 시간 또한 분석에서 고려되었다. 시스템은 전개에 있어 변수 값들에 따라 고정점, 한계주기 그리고 카오스(Chaos)적인 행태와 같은 서로 다른 결과를 보여 주었다. 발생된 시계열의 추계학적인 행태는 궤적들이 초기 조거넹 매우 민감한 한정된 수의 방정식을 가지는 비선형 동력학 시스템으로부터 발생하는 확정론적 카오스 때문이다. 강우의 특성으로부터 발생하는 잡음은 어트랙터(Attractor)의 조직화된 구조를 파괴시키는데, 잡음의 존재에도 불구하고 어트랙터가 존재한다는 것은 시스템의 전개의 다기 예측에 있어 매우 중요하다고 할 수가 있다. 이러한 비선형 동력계가 가지고 있는 의미는 수문자료나 현상들의 해석과 모델링에 있어 중요하다.