• 한국지능시스템학회논문지
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• 제18권4호
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• pp.482-487
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• 2008

침수의 경우에, 수중 비행체(UFV : Underwater Flight Vehicle)는 발라스트 탱크들의 내부를 고압 공기로 비워 내어 부상을 수행한다. 동시에, 침수와 부상 순차에 의한 오버슈트 심도를 감소시키기 위해서 제어판과 추진기를 병행하여 사용한다. 그런데, 기존의 전체 고압 공기 blow-off 방법은 가벼운 침수일지라도 부상 후에는 몸체를 수면에 드러나게 한다. 이는 불필요한 임무 실패 또는 몸체 노출의 결과를 가져온다. 따라서, 부상 제어에 의해 오버슈트 심도를 감소시킴과 동시에 몸체를 수면 근처에 유지시키는 것이 필요하다. 이 문제를 해결하기 위해서 심도 제어에 있어서의 전문가 지식을 확장하는 분해법 및 FBFE(Fuzzy Basis Function Expansion)을 사용하는 적응법에 기초한 적응 부상 제어 알고리즘이 제안되었다. 제안된 알고리즘의 성능을 검증하기 위해 UFV 부상 제어가 수행되었다. 시뮬레이션 결과는 제안된 알고리즘이 UFV 부상제어 시스템에 존재하는 문제점들을 온라인으로 효과적으로 해결하고 있음을 보여준다.

• Geomechanics and Engineering
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• 제18권5호
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• pp.515-525
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• 2019

A karst collapse, as a natural hazard, is totally different to a normal collapse. In recent years, karst collapses have caused substantial economic losses and even threatened human safety. A risk assessment model for karst collapse was developed based on the fuzzy analytic hierarchy process (FAHP) and grey relational analysis (GRA), which is a simple and effective mathematical algorithm. An evaluation index played an important role in the process of completing the risk assessment model. In this study, the proposed model was applied to Jiaobai village in southwest China. First, the main controlling factors were summarized as an evaluation index of the model based on an investigation and statistical analysis of the natural formation law of karst collapse. Second, the FAHP was used to determine the relative weights and GRA was used to calculate the grey relational coefficient among the indices. Finally, the relational sequence of evaluation objects was established by calculating the grey weighted relational degree. According to the maximum relational rule, the greater the relational degree the better the relational degree with the hierarchy set. The results showed that the model accurately simulated the field condition. It is also demonstrated the contribution of various control factors to the process of karst collapse and the degree of collapse in the study area.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제4권1호
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• pp.23-28
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• 2004

This paper proposes a sensor-fusion technique where the data sets for the previous moments are properly transformed and fused into the current data sets to enable accurate measurement, such as, distance to an obstacle and location of the service robot itself. In the conventional fusion schemes, the measurement is dependent on the current data sets. As the results, more of sensors are required to measure a certain physical parameter or to improve the accuracy of the measurement. However, in this approach, instead of adding more sensors to the system, the temporal sequence of the data sets are stored and utilized for the measurement improvement. Theoretical basis is illustrated by examples and the effectiveness is proved through the simulations. Finally, the new space and time sensor fusion(STSF) scheme is applied to the control of a mobile robot in an unstructured environment as well as structured environment.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제11권3호
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• pp.135-142
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• 2011

Unlike using the sequence-based representation for a chromosome in previous genetic algorithms for Bayesian structure learning, we proposed a matrix representation-based genetic algorithm. Since a good chromosome representation helps us to develop efficient genetic operators that maintain a functional link between parents and their offspring, we represent a chromosome as a matrix that is a general and intuitive data structure for a directed acyclic graph(DAG), Bayesian network structure. This matrix-based genetic algorithm enables us to develop genetic operators more efficient for structuring Bayesian network: a probability matrix and a transpose-based mutation operator to inherit a structure with the correct edge direction and enhance the diversity of the offspring. To show the outstanding performance of the proposed method, we analyzed the performance between two well-known genetic algorithms and the proposed method using two Bayesian network scoring measures.

• Journal of information and communication convergence engineering
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• 제6권4호
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• pp.444-447
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• 2008

In this paper, we proposed the recognition system of car license plates to mitigate traffic problems. The processing sequence of the proposed algorithm is as follows. At first, a license plate segment is extracted from an acquired car image using morphological features and color information, and noises are eliminated from the extracted license plate segment using line scan algorithm and Grassfire algorithm, and then individual codes are extracted from the license plate segment using edge tracking algorithm. Finally the extracted individual codes are recognized by an FCM algorithm. In order to evaluate performance of segment extraction and code recognition of the proposed method, we used 100 car images for experiment. In the results, we could verify the proposed method is more effective and recognition performance is improved in comparison with conventional car license plate recognition methods.

• Journal of Electrical Engineering and Technology
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• 제10권4호
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• pp.1910-1914
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• 2015

Human posture recognition is an attractive and challenging topic in computer vision due to its promising applications in the areas of personal health care, environmental awareness, human-computer-interaction and surveillance systems. Human posture recognition in video sequences consists of two stages: the first stage is training and evaluation and the second is deployment. In the first stage, the system is trained and evaluated using datasets of human postures to ‘teach’ the system to classify human postures for any future inputs. When the training and evaluation process is deemed satisfactory as measured by recognition rates, the trained system is then deployed to recognize human postures in any input video sequence. Different classifiers were used in the training such as Multilayer Perceptron Feedforward Neural networks, Self-Organizing Maps, Fuzzy C Means and K Means. Results show that supervised learning classifiers tend to perform better than unsupervised classifiers for the case of human posture recognition.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 제36회 하계학술대회 논문집 A
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• pp.178-180
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• 2005

Recently, electrical demands increase rapidly in metropolitan areas according to the extension of urban areas. Therefore underground transmission lines are getting expanded. This paper presents the rapid and accurate algorithm for fault discrimination and fault location in underground transmission lines. This paper uses fuzzy logic method using voltage and zero sequence for fault discrimination. And this paper uses travelling wave and wavelet transform for fault location. To prove the performance of the algorithm, it test algorithm with signal obtained from ATPDraw simulation.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 추계학술대회 논문집 전력기술부문
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• pp.350-352
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• 2005

Recently, electrical demands increase rapidly in metropolitan areas according to the extension of urban areas. Therefore underground transmission lines are getting expanded. This paper presents the rapid and accurate algorithm for fault discrimination and fault location in underground transmission lines. This paper uses fuzzy logic method using voltage and zero sequence for fault discrimination. And this paper uses travelling wave and wavelet transform for fault location. To prove the performance of the algorithm, it test algorithm with signal obtained from ATPDraw simulation.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제3권2호
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• pp.239-243
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• 2003

Recently, there has been active research conducted on the intelligent agent in various fields. The results have been widely applied to intelligent user-friendly interfaces. In this system, we modeled, designed, and implemented an intelligent agent system that can be applied to stock and news. Some procedures such as login sequence to the web site, process to get stock information, setting stock in concern, intelligent news system module, news analysis module, and news learning module are modeled in detail and described in block diagram level. In our experiment on stock system, it showed quite a useful alarming screen avatar result and also on news system. it successfully rearranged the order of the news according to the user's preferences.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제3권1호
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• pp.87-92
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• 2003

This paper describes a system for tracking multiple faces in an input video sequence using facial convex hull based facial segmentation and robust hausdorff distance. The algorithm adapts skin color reference map in YCbCr color space and hair color reference map in RGB color space for classifying face region. Then, we obtain an initial face model with preprocessing and convex hull. For tracking, this algorithm computes displacement of the point set between frames using a robust hausdorff distance and the best possible displacement is selected. Finally, the initial face model is updated using the displacement. We provide an example to illustrate the proposed tracking algorithm, which efficiently tracks rotating and zooming faces as well as existing multiple faces in video sequences obtained from CCD camera.