Improved GART Neural Network Model for Pattern Classification and Rule Extraction With Application to Power Systems
暂无分享,去创建一个
Chee Peng Lim | Mau Teng Au | Keem Siah Yap | K. S. Yap | C. Lim | M. T. Au
[1] V. Miranda,et al. An interpretation of neural networks as inference engines with application to transformer failure diagnosis , 2004, 2004 International Conference on Probabilistic Methods Applied to Power Systems.
[2] Shing Chiang Tan,et al. Application of an adaptive neural network with symbolic rule extraction to fault detection and diagnosis in a power generation plant , 2004, IEEE Transactions on Energy Conversion.
[3] Paramasivan Saratchandran,et al. Performance evaluation of a sequential minimal radial basis function (RBF) neural network learning algorithm , 1998, IEEE Trans. Neural Networks.
[4] B. Efron. Nonparametric standard errors and confidence intervals , 1981 .
[5] V. Miranda,et al. Knowledge discovery in neural networks with application to transformer failure diagnosis , 2005, IEEE Transactions on Power Systems.
[6] Chee Peng Lim,et al. A Hybrid Art-grnn Online Learning Neural Network with a -insensitive Loss Function , 2022 .
[7] Michael Margaliot,et al. Knowledge extraction from a class of support vector machines using the fuzzy all-permutations rule-base , 2011, 2011 IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB).
[8] A. De,et al. A fuzzy ARTMAP fault classifier for impulse testing of power transformers , 2004, IEEE Transactions on Dielectrics and Electrical Insulation.
[9] E. Parzen. On Estimation of a Probability Density Function and Mode , 1962 .
[10] R. Rogers. IEEE and IEC Codes to Interpret Incipient Faults in Transformers, Using Gas in Oil Analysis , 1978, IEEE Transactions on Electrical Insulation.
[11] Joachim Diederich,et al. The truth will come to light: directions and challenges in extracting the knowledge embedded within trained artificial neural networks , 1998, IEEE Trans. Neural Networks.
[12] T. Funabashi,et al. Next day load curve forecasting using hybrid correction method , 2005, IEEE Transactions on Power Systems.
[13] Henry Wu,et al. Evidential Reasoning In Dissolved Gas Analysis For Power Transformers , 2006 .
[14] Brian Lithgow,et al. New Fault Diagnosis of Circuit Breakers , 2002, IEEE Power Engineering Review.
[15] Chia-Hung Lin,et al. Adaptive wavelet networks for power-quality detection and discrimination in a power system , 2006 .
[16] M. Duval,et al. Improving the reliability of transformer gas-in-oil diagnosis , 2005, IEEE Electrical Insulation Magazine.
[17] Chih-Jen Lin,et al. A study on reduced support vector machines , 2003, IEEE Trans. Neural Networks.
[18] N. Amjady. Day-ahead price forecasting of electricity markets by a new fuzzy neural network , 2006, IEEE Transactions on Power Systems.
[19] Patrice Wira,et al. A Unified Artificial Neural Network Architecture for Active Power Filters , 2007, IEEE Transactions on Industrial Electronics.
[20] Boaz Lerner,et al. The Bayesian ARTMAP , 2007, IEEE Transactions on Neural Networks.
[21] Y. C. Huang. A New Data Mining Approach to Dissolved Gas Analysis of Oil-Insulated Power Apparatus , 2002, IEEE Power Engineering Review.
[22] Hong-Tzer Yang,et al. Abductive network model-based diagnosis system for power transformer incipient fault detection , 2002 .
[23] Ah-Hwee Tan,et al. Rule Extraction: From Neural Architecture to Symbolic Representation , 1995 .
[24] J. L. Guardado,et al. A Comparative Study of Neural Network Efficiency in Power Transformers Diagnosis Using Dissolved Gas Analysis , 2001, IEEE Power Engineering Review.
[25] Noel E. Sharkey,et al. A Multi-Net System for the Fault Diagnosis of a Diesel Engine , 2000, Neural Computing & Applications.
[26] Ignacio Requena,et al. Are artificial neural networks black boxes? , 1997, IEEE Trans. Neural Networks.
[27] Stephen Grossberg,et al. Fuzzy ART: Fast stable learning and categorization of analog patterns by an adaptive resonance system , 1991, Neural Networks.
[28] David Hinkley,et al. Bootstrap Methods: Another Look at the Jackknife , 2008 .
[29] James R. Williamson,et al. Gaussian ARTMAP: A Neural Network for Fast Incremental Learning of Noisy Multidimensional Maps , 1996, Neural Networks.
[30] Wei Chu,et al. Bayesian support vector regression using a unified loss function , 2004, IEEE Transactions on Neural Networks.
[31] Heekuck Oh,et al. Neural Networks for Pattern Recognition , 1993, Adv. Comput..
[32] Jyh-Shing Roger Jang,et al. ANFIS: adaptive-network-based fuzzy inference system , 1993, IEEE Trans. Syst. Man Cybern..
[33] Sergios Theodoridis,et al. A geometric approach to Support Vector Machine (SVM) classification , 2006, IEEE Transactions on Neural Networks.
[34] Richard O. Duda,et al. Pattern classification and scene analysis , 1974, A Wiley-Interscience publication.
[35] Donald F. Specht,et al. A general regression neural network , 1991, IEEE Trans. Neural Networks.
[36] Michael Margaliot,et al. Are artificial neural networks white boxes? , 2005, IEEE Transactions on Neural Networks.
[37] D. Agoris,et al. Method Combining ANNs and Monte Carlo Simulation for the Selection of the Load Shedding Protection Strategies in Autonomous Power Systems , 2006, IEEE Transactions on Power Systems.
[38] Chia-Hung Lin,et al. Adaptive wavelet networks for power-quality detection and discrimination in a power system , 2006, IEEE Transactions on Power Delivery.
[39] Chee Peng Lim,et al. A modified fuzzy min-max neural network with rule extraction and its application to fault detection and classification , 2008, Appl. Soft Comput..
[40] Pedro J. Zufiria,et al. Design and comparison of adaptive power system stabilizers based on neural fuzzy networks and genetic algorithms , 2007, Neurocomputing.
[41] Stephen Grossberg,et al. Fuzzy ARTMAP: A neural network architecture for incremental supervised learning of analog multidimensional maps , 1992, IEEE Trans. Neural Networks.
[42] Chih-Jen Lin,et al. LIBSVM: A library for support vector machines , 2011, TIST.
[43] Narasimhan Sundararajan,et al. An efficient sequential learning algorithm for growing and pruning RBF (GAP-RBF) networks , 2004, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[44] Jung-Hsien Chiang,et al. Support vector learning mechanism for fuzzy rule-based modeling: a new approach , 2004, IEEE Transactions on Fuzzy Systems.
[45] Furong Li,et al. A novel approach to fault diagnosis in multicircuit transmission lines using fuzzy ARTmap neural networks , 1999, IEEE Trans. Neural Networks.
[46] Pavel Pudil,et al. Introduction to Statistical Pattern Recognition , 2006 .
[47] Issam Dagher,et al. An ordering algorithm for pattern presentation in fuzzy ARTMAP that tends to improve generalization performance , 1999, IEEE Trans. Neural Networks.
[48] Chee Peng Lim,et al. A hybrid neural network model for rule generation and its application to process fault detection and diagnosis , 2007, Eng. Appl. Artif. Intell..
[49] Paulo F. Ribeiro,et al. Impact of Aggregate Linear Load Modeling on Harmonic Analysis: A Comparison of Common Practice and Analytical Models , 2003, IEEE Power Engineering Review.
[50] Josef Kittler,et al. Pattern recognition : a statistical approach , 1982 .
[51] Michel Duval,et al. Interpretation of gas-in-oil analysis using new IEC publication 60599 and IEC TC 10 databases , 2001 .