Browse > Article

Tracking Detection using Information Granulation-based Fuzzy Radial Basis Function Neural Networks  

Choi, Jeoung-Nae (대림대학 전기과)
Kim, Young-Il (대림대학 전기과)
Oh, Sung-Kwun (수원대학 전기공학과)
Kim, Jeong-Tae (대진대 공대 전기정보시스템공학과)
Publication Information
The Transactions of The Korean Institute of Electrical Engineers / v.58, no.12, 2009 , pp. 2520-2528 More about this Journal
Abstract
In this paper, we proposed tracking detection methodology using information granulation-based fuzzy radial basis function neural networks (IG-FRBFNN). According to IEC 60112, tracking device is manufactured and utilized for experiment. We consider 12 features that can be used to decide whether tracking phenomenon happened or not. These features are considered by signal processing methods such as filtering, Fast Fourier Transform(FFT) and Wavelet. Such some effective features are used as the inputs of the IG-FRBFNN, the tracking phenomenon is confirmed by using the IG-FRBFNN. The learning of the premise and the consequent part of rules in the IG-FRBFNN is carried out by Fuzzy C-Means (FCM) clustering algorithm and weighted least squares method (WLSE), respectively. Also, Hierarchical Fair Competition-based Parallel Genetic Algorithm (HFC-PGA) is exploited to optimize the IG-FRBFNN. Effective features to be selected and the number of fuzzy rules, the order of polynomial of fuzzy rules, the fuzzification coefficient used in FCM are optimized by the HFC-PGA. Tracking inference engine is implemented by using the LabVIEW and loaded into embedded system. We show the superb performance and feasibility of the tracking detection system through some experiments.
Keywords
Tracking; Radial Basis Function Neural Networks; Fuzzy C-Means clustering; Hierarchical Fair Competition-based Parallel Genetic Algorithm; Weighted Least Squares Estimator;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
Times Cited By SCOPUS : 0
연도 인용수 순위
1 S.-K. Oh and W. Pedrycz, 'Identification of Fuzzy Systems by means of an Auto- Tuning Algorithm and Its Application to Nonlinear Systems,' Fuzzy Sets and Syst., Vol. 115, No.2, pp. 205-230, 2000   DOI   ScienceOn
2 J. S. R. Jang, 'ANFIS: Adaptive-Network-Based Fuzzy Inference System,' IEEE Trans. System, Man, and Cybern., Vol. 23, No.3, pp. 665-685, 1993   DOI   ScienceOn
3 최대원, 이오걸, 김석순, '신경회로망을 이용한 옥내배선의 트랙킹 검지 기법', 대한화재 소방학회지, Vol. 9, No. 1, pp. 3-9, 1995   과학기술학회마을
4 IEC 60112, 'Method for the determination of the proof and the comparative tracking indices of solid insulating materials', 2004
5 P. R. Krishnaiah and L. N. Kanal, editors. Classification, pattern recognition, and reduction of dimensionality, Vol. 2 of Handbook of Statistics. North-Holland, Amsterdam, 1982
6 J.J. Hu, E.D. Goodman, The Hierarchical Fair competition (HFC) Model for Parallel Evolutionary Algortihms, CEC 2002 - Proceedings of the 2002 congress on Evolutionary Computation, IEEE, Honolulu, Hawaii (2002) 45-94   DOI
7 A. Staiano. J. Tagliaferri, W. Pedrycz, 'Improving RBF networks performance in regression tasks by means of a supervised fuzzy clusering'Automatic structure and parameter,' Neurocomputing, Vol. 69, pp. 1570-1581, 2006   DOI   ScienceOn
8 J.N. Choi, S.K. Oh, W. Pedrycz, Structural and parametric design of fuzzy inference systems using hierarchical fair competition -based parallel genetic algorithm and infonnation granulation, International Journal of Approximate Reasoning 49 (2008) 631-648   DOI   ScienceOn
9 최충석, 송길목, 김형래, 김향곤, 김동욱, 김동우, '트래킹에 의해 열화된 누전차단기 외함의 특성분석', 2002 한국화재 소방학회 추계학술논문, pp. 47-52   과학기술학회마을
10 L. X. Wang, J. M. Mendel, 'Generating fuzzy rules from numerical data with applications,' IEEE Trans. Systems, Man, Cybern., Vol. 22, No.6, pp. 1414-1427, 1992   DOI   ScienceOn
11 최정내, 김현기, 오성권, 'PSO를 이용한 FCM 기반 RBF 뉴럴네트워크의 최적화', 대한전기학회지, Vol. 57, No. 1, pp.2108-2116, 2008   과학기술학회마을
12 L. P. Maguire, B. Roche, T. M. McGinnity, L. J. McDaid, 'Predicting a chaotic time series using a fuzzy neural network,' Information Sciences, Vol. 112, pp. 125-136, 1998   DOI   ScienceOn
13 지승욱, 이상훈, 김충년, 이춘하, 이광식, '트래킹 검출을 위한 주파수-시간 분석(분할-FFT)', 대한전기학회논문지, Vol. 53c, No. 10, pp. 530-538, 2004   과학기술학회마을
14 J.J. Hu, E.D. Goodman, K. S. S대, M. Pei, Adaptive Hierarchical Fair competition (AHFC) Model for Parallel Evolutionary Algorithms, GECCO 2002 - Genetic and Evolutionary Computation Conference (2002) 772-779
15 최원은, 조기선, 이승우, '고분자 절연재료의 트랙킹 현상에 관한 연구', 전기학회논문지, Vol. 34, No. 12, pp. 457-463, 1985
16 최정내, 오성권, 김현기, 'FCM 기반 퍼지 뉴럴 네트워크의 진화론적 최적화', 대한전기학회지, Vol. 57, No. 3, pp. 466-472, 2008   과학기술학회마을
17 W. Pderyca and G. Vukovich, 'Granular neural networks,' Neurocomputing, Vol. 36, pp. 205-224, 2001   DOI   ScienceOn
18 지승욱, 이춘하, 윤대희, 송현직, 심광열, 박원주, 이광식, '전압파형을 이용한 트래킹 진전과정 분석방법에 관한 연구', 조명.전기설비학회논문지, Vol. 20, No. 8, pp. 30-35, 2006   과학기술학회마을   DOI   ScienceOn