• International Journal of Fuzzy Logic and Intelligent Systems
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• 제10권2호
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• pp.101-106
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• 2010

We propose an approach to estimate the real-time moving trajectory of an object in this paper. The object's position is obtained from the image data of a CCD camera, while a state estimator predicts the linear and angular velocities of the moving object. To overcome the uncertainties and noises residing in the input data, a Extended Kalman Filter(EKF) and neural networks are utilized cooperatively. Since the EKF needs to approximate a nonlinear system into a linear model in order to estimate the states, there still exist errors as well as uncertainties. To resolve this problem, in this approach the Kohonen networks, which have a high adaptability to the memory of the inputoutput relationship, are utilized for the nonlinear region. In addition to this, the Kohonen network, as a sort of neural network, can effectively adapt to the dynamic variations and become robust against noises. This approach is derived from the observation that the Kohonen network is a type of self-organized map and is spatially oriented, which makes it suitable for determining the trajectories of moving objects. The superiority of the proposed algorithm compared with the EKF is demonstrated through real experiments.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제12권2호
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• pp.181-186
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• 2012

This paper proposes a method for evaluating web pages by considering implicit user reaction on web pages. Usually users spend more time and make more reactions, such as clicking, dragging and scrolling, while reading interesting pages. Based on this observation, a web page evaluation method by observing implicit user reaction is proposed. The system is designed with Ajax for observing user reactions, and neural networks for learning correlation between user reactions and usefulness of pages. The amounts of each type of user reactions are inputted to neural networks. Also the numbers of characters and images of pages are used as inputs because the amount of users' behaviors has a tendency to increase as the length of pages increase. The experiment is conducted with 113 people and 74 pages. Each page is ranked by users with a questionnaire. The proposed method shows more close ranking results to the user ranks than Google. That is, our system evaluates web pages more closely to users' viewpoint than Google. Although our experiment is limited, our result shows powerful potential of new element for web page evaluation. Some approaches evaluate web pages with their contents and some evaluate web pages with structural attributes, particularly links, of pages. Web page evaluation is for users, so the best evaluation can be done by users themselves. So, user feedback is one of the most important factors for web page evaluation. This paper proposes a new method which reflects user feedbacks on web pages.

• 조명전기설비학회논문지
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• 제23권2호
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• pp.70-76
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• 2009

최근 경제적 시간적 이유로 전력기기의 운전 중 부분방전 감시진단 장치가 많이 이용되는 추세에 있으나, 시 공간적으로 다양한 종류의 잡음의 영향이 문제시되고 있다. 이에 여러가지 잡음제거 기법들이 개발되었으나 범용적이지 않고 설정이나 환경에 따라 성능이 상이하다. 본 논문에서는 부분방전 측정신호의 잡음포함 정도를 수치적으로 제시할 수 있는 방법을 제시하였다. 이 기법이 적용되어 개발된 알고리즘을 이용하여, 다수 잡음제거 기법의 설정에 따른 다양한 결과 중 최선의 결과를 자동적으로 선택할 수 있었다. 운전 중 부분방전 감시진단 시스템에 사용되는 세 가지 잡음제거 기법에 적용하여 성공적으로 복합화 하였고, 국내 다양한 잡음 환경의 고전압 기기들로부터 실측한 데이터에 능동적으로 적응한 잡음제거 결과를 도출할 수 있었다.