Effectiveness of Partition and Graph Theoretic Clustering Algorithms for Multiple Source Partial Discharge Pattern Classification Using Probabilistic Neural Network and Its Adaptive Version: A Critique Based on Experimental Studies
暂无分享,去创建一个
[1] R. Candela,et al. PD recognition by means of statistical and fractal parameters and a neural network , 2000 .
[2] Alain Bretto,et al. Introduction to Hypergraph Theory and Its Use in Engineering and Image Processing , 2004 .
[3] N. K. Bose,et al. Neural Network Fundamentals with Graphs, Algorithms and Applications , 1995 .
[4] D. F. Specht,et al. Probabilistic neural networks for classification, mapping, or associative memory , 1988, IEEE 1988 International Conference on Neural Networks.
[5] A. Krivda,et al. Recognition of discharges: Discrimination and classification , 1995 .
[6] Donald F. Specht,et al. Probabilistic neural networks and the polynomial Adaline as complementary techniques for classification , 1990, IEEE Trans. Neural Networks.
[7] Xiandong Ma,et al. Interpretation of wavelet analysis and its application in partial discharge detection , 2002 .
[8] R. Bartnikas,et al. Trends in partial discharge pattern classification: a survey , 2005, IEEE Transactions on Dielectrics and Electrical Insulation.
[9] Bernhard Schölkopf,et al. Learning with Hypergraphs: Clustering, Classification, and Embedding , 2006, NIPS.
[10] B. T. Phung,et al. Development of computer-based measurements and their application to PD pattern analysis , 1995 .
[11] G. Montanari,et al. Digital detection and fuzzy classification of partial discharge signals , 2002 .
[12] B. Karthikeyan,et al. ART 2 - an unsupervised neural network for PD pattern recognition and classification , 2006, Expert Syst. Appl..
[13] Magdy M. A. Salama,et al. Discrimination between PD pulse shapes using different neural network paradigms , 1994 .
[14] Magdy M. A. Salama,et al. Partial discharge pattern classification using the fuzzy decision tree approach , 2005, IEEE Transactions on Instrumentation and Measurement.
[15] Jong-Sheng Cherng,et al. A hypergraph based clustering algorithm for spatial data sets , 2001, Proceedings 2001 IEEE International Conference on Data Mining.
[16] Vance Faber,et al. Clustering and the continuous k-means algorithm , 1994 .
[17] R. Bartnikas,et al. Partial discharge pulse pattern recognition using Hidden Markov Models , 2004, IEEE Transactions on Dielectrics and Electrical Insulation.
[18] June-Ho Lee,et al. Classification of PD patterns from multiple defects , 2000, Proceedings of the 6th International Conference on Properties and Applications of Dielectric Materials (Cat. No.00CH36347).
[19] L. Satish,et al. Use of hidden Markov models for partial discharge pattern classification , 1993 .
[20] E. M. Lalitha,et al. Wavelet analysis for classification of multi-source PD patterns , 2000 .
[21] TaeHyun Hwang,et al. A hypergraph-based learning algorithm for classifying gene expression and arrayCGH data with prior knowledge , 2009, Bioinform..
[22] L. Satish,et al. Can fractal features be used for recognizing 3-d partial discharge patterns , 1995 .
[23] Ray Bartnikas,et al. Partial discharges. Their mechanism, detection and measurement , 2002 .
[24] R. Fisher. THE USE OF MULTIPLE MEASUREMENTS IN TAXONOMIC PROBLEMS , 1936 .
[25] L. Satish,et al. Artificial neural networks for recognition of 3-d partial discharge patterns , 1994 .
[26] E. Gulski. Digital analysis of partial discharges , 1995 .
[27] M.N.S. Swamy,et al. Neural networks in a softcomputing framework , 2006 .
[28] Way-Soong Lim,et al. A new method of reducing network complexity in probabilistic neural network for target identification , 2004, IEICE Electron. Express.
[29] D. F. Specht,et al. Generalization accuracy of probabilistic neural networks compared with backpropagation networks , 1991, IJCNN-91-Seattle International Joint Conference on Neural Networks.
[30] Timothy Masters,et al. Advanced algorithms for neural networks: a C++ sourcebook , 1995 .
[31] E. M. Lalitha,et al. Fractal image compression for classification of PD sources , 1998 .
[32] S. Gopal,et al. Orthogonal least square center selection technique - A robust scheme for multiple source Partial Discharge pattern recognition using Radial Basis Probabilistic Neural Network , 2011, Expert Syst. Appl..
[33] Laurene V. Fausett,et al. Fundamentals Of Neural Networks , 1994 .
[34] R. J. Van Brunt,et al. Importance of unraveling memory propagation effects in interpreting data on partial discharge statistics , 1993 .
[35] Srinivasan Gopal,et al. PNN AND ITS ADAPTIVE VERSION -- AN INGENIOUS APPROACH TO PD PATTERN CLASSIFICATION COMPARED WITH BPA NETWORK , 2006 .
[36] B. Karthikeyan,et al. Probabilistic Neural Network and its Adaptive Version - a Stochastic Approach to PD Pattern Classification Task , 2005, Int. J. Inf. Acquis..
[37] S Venkatesh,et al. A heuristic complex probabilistic neural network system for partial discharge pattern classification , 2013 .
[38] M.N. Narayanachar,et al. Pulse sequence studies on PD data , 2002, Annual Report Conference on Electrical Insulation and Dielectric Phenomena.
[39] D. F. Specht,et al. Experience with adaptive probabilistic neural networks and adaptive general regression neural networks , 1994, Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94).
[40] Rui Xu,et al. Survey of clustering algorithms , 2005, IEEE Transactions on Neural Networks.
[41] E. Gulski,et al. Neural networks as a tool for recognition of partial discharges , 1993 .
[42] Bernd Freisleben,et al. PD source identification with novel discharge parameters using counterpropagation neural networks , 1997 .
[43] Pietro Burrascano,et al. Learning vector quantization for the probabilistic neural network , 1991, IEEE Trans. Neural Networks.
[44] S. Gopal,et al. Robust Heteroscedastic Probabilistic Neural Network for multiple source partial discharge pattern recognition - Significance of outliers on classification capability , 2011, Expert Syst. Appl..
[45] Chi Hau Chen,et al. Fuzzy logic and neural network handbook , 1996 .
[46] M. Salama,et al. PD pattern recognition with neural networks using the multilayer perceptron technique , 1993 .
[47] Magdy M. A. Salama,et al. Determination of neural-network topology for partial discharge pulse pattern recognition , 2002, IEEE Trans. Neural Networks.
[48] B. Karthikeyan,et al. Partial discharge pattern classification using composite versions of probabilistic neural network inference engine , 2008, Expert Syst. Appl..
[49] Richard J. Van Brunt. Stochastic Properties of Partial-Discharge Phenomena: A Review , 1991 .
[50] A. Krivda,et al. Automated recognition of partial discharges , 1995 .