Estimation and generation of training patterns for control chart pattern recognition
暂无分享,去创建一个
[1] Wee Ser,et al. Probabilistic neural-network structure determination for pattern classification , 2000, IEEE Trans. Neural Networks Learn. Syst..
[2] D. Pham,et al. THE BEES ALGORITHM, A NOVEL TOOL FOR COMPLEX OPTIMISATION PROBLEMS , 2006 .
[3] Kurt Hornik,et al. kernlab - An S4 Package for Kernel Methods in R , 2004 .
[4] Mahmoud A. Barghash,et al. Pattern recognition of control charts using artificial neural networks—analyzing the effect of the training parameters , 2004, J. Intell. Manuf..
[5] Ruey-Shiang Guh,et al. A hybrid learning-based model for on-line detection and analysis of control chart patterns , 2005, Comput. Ind. Eng..
[6] Corinna Cortes,et al. Support-Vector Networks , 1995, Machine Learning.
[7] Daphne Koller,et al. Support Vector Machine Active Learning with Applications to Text Classification , 2000, J. Mach. Learn. Res..
[8] Donald F. Specht,et al. Probabilistic neural networks , 1990, Neural Networks.
[9] Marco Castellani,et al. Evolutionary generation of neural network classifiers - An empirical comparison , 2013, Neurocomputing.
[10] B. McKay,et al. Probabilistic neural network array architecture for ECG classification , 1995, Proceedings of 17th International Conference of the Engineering in Medicine and Biology Society.
[11] Jun Lv,et al. Recognition of concurrent control chart patterns using wavelet transform decomposition and multiclass support vector machines , 2013, Comput. Ind. Eng..
[12] Ruey-Shiang Guh. Optimizing Feedforward Neural Networks For Control Chart Pattern Recognition Through Genetic Algorithms , 2004, Int. J. Pattern Recognit. Artif. Intell..
[13] S. Gunn. Support Vector Machines for Classification and Regression , 1998 .
[14] Anurag Pande,et al. A Computing Approach Using Probabilistic Neural Networks for Instantaneous Appraisal of Rear‐End Crash Risk , 2008, Comput. Aided Civ. Infrastructure Eng..
[15] Pingyu Jiang,et al. Recognizing control chart patterns with neural network and numerical fitting , 2009, J. Intell. Manuf..
[16] Ruey-Shiang Guh,et al. Integrating artificial intelligence into on‐line statistical process control , 2003 .
[17] Mik Wisniewski,et al. Applied Regression Analysis: A Research Tool , 1990 .
[18] D. F. Specht,et al. Enhancements to probabilistic neural networks , 1992, [Proceedings 1992] IJCNN International Joint Conference on Neural Networks.
[19] Takuji Nishimura,et al. Mersenne twister: a 623-dimensionally equidistributed uniform pseudo-random number generator , 1998, TOMC.
[20] Duc Truong Pham,et al. APPLICATION OF THE BEES ALGORITHM TO THE TRAINING OF RADIAL BASIS FUNCTION NETWORKS FOR CONTROL CHART PATTERN RECOGNITION , 2006 .
[21] Way Kuo,et al. Identification of control chart patterns using wavelet filtering and robust fuzzy clustering , 2007, J. Intell. Manuf..
[22] Massimo Pacella,et al. Manufacturing quality control by means of a Fuzzy ART network trained on natural process data , 2004, Eng. Appl. Artif. Intell..
[23] Zhirong Sun,et al. Support vector machine approach for protein subcellular localization prediction , 2001, Bioinform..
[24] R. Brereton,et al. Support vector machines for classification and regression. , 2010, The Analyst.
[25] A. McQuarrie,et al. Regression and Time Series Model Selection , 1998 .
[26] Richard F. Gunst,et al. Applied Regression Analysis , 1999, Technometrics.
[27] Duc Truong Pham,et al. Benchmarking and comparison of nature-inspired population-based continuous optimisation algorithms , 2014, Soft Comput..
[28] Duc Truong Pham,et al. Feature-based control chart pattern recognition , 1997 .
[29] R Core Team,et al. R: A language and environment for statistical computing. , 2014 .
[30] Petros Xanthopoulos,et al. A weighted support vector machine method for control chart pattern recognition , 2014, Comput. Ind. Eng..
[31] Ahmed Ghorbel,et al. A survey of control-chart pattern-recognition literature (1991-2010) based on a new conceptual classification scheme , 2012, Comput. Ind. Eng..
[32] Ahmed Shaban,et al. A double neural network approach for the identification and parameter estimation of control chart patterns , 2012 .
[33] Mo M. Jamshidi,et al. A Modified Probabilistic Neural Network for Partial Volume Segmentation in Brain MR Image , 2007, IEEE Transactions on Neural Networks.
[34] S. Gauri. Improved feature-based test statistic for assessing suitability of the preliminary samples for constructing control limits of $$ \bar{X} $$ chart , 2012 .
[35] Chih-Jen Lin,et al. A comparison of methods for multiclass support vector machines , 2002, IEEE Trans. Neural Networks.
[36] David S. Touretzky,et al. Optical Chinese character recognition using probabilistic neural networks , 1997, Pattern Recognit..
[37] Patrick Haffner,et al. Support vector machines for histogram-based image classification , 1999, IEEE Trans. Neural Networks.
[38] F. Gubina,et al. Allocation of the load profiles to consumers using probabilistic neural networks , 2005, IEEE Transactions on Power Systems.
[39] Nello Cristianini,et al. Support vector machine classification and validation of cancer tissue samples using microarray expression data , 2000, Bioinform..
[40] Susanta Kumar Gauri. Control chart pattern recognition using feature-based learning vector quantization , 2010 .
[41] Elif Derya Übeyli. Lyapunov exponents/probabilistic neural networks for analysis of EEG signals , 2010, Expert Syst. Appl..
[42] S. A. Lesany,et al. Recognition and classification of single and concurrent unnatural patterns in control charts via neural networks and fitted line of samples , 2014 .
[43] Andreas Christmann,et al. Support vector machines , 2008, Data Mining and Knowledge Discovery Handbook.
[44] Massimiliano Pontil,et al. Support Vector Machines for 3D Object Recognition , 1998, IEEE Trans. Pattern Anal. Mach. Intell..
[45] Saeid Nahavandi,et al. Identification of concurrent control chart patterns with singular spectrum analysis and learning vector quantization , 2013, J. Intell. Manuf..
[46] Yung-Nien Sun,et al. Ultrasonic image analysis for liver diagnosis , 1996 .
[47] Saeid Nahavandi,et al. Concurrent control chart patterns recognition with singular spectrum analysis and support vector machine , 2013, Comput. Ind. Eng..
[48] Dong Hyawn Kim,et al. Application of probabilistic neural network to design breakwater armor blocks , 2008 .
[49] Jin-Juan Quan,et al. Multiscale probabilistic neural network method for SAR image segmentation , 2008, Appl. Math. Comput..
[50] Shaoxiong Wu. Abnormal Pattern Parameters Estimation of Control Chart Based on Wavelet Transform and Probabilistic Neural Network , 2006 .
[51] Shankar Chakraborty,et al. Recognition of control chart patterns using improved selection of features , 2009, Comput. Ind. Eng..
[52] Adnan Hassan,et al. An improved scheme for online recognition of control chart patterns , 2011, Int. J. Comput. Aided Eng. Technol..
[53] Elif Derya íbeyli. Lyapunov exponents/probabilistic neural networks for analysis of EEG signals , 2010 .
[54] A. Ebrahimzadeh,et al. Application of the PSO-SVM model for recognition of control chart patterns. , 2010, ISA transactions.
[55] A. Gallant,et al. Nonlinear Statistical Models , 1988 .
[56] Yuehjen E. Shao,et al. Mixture control chart patterns recognition using independent component analysis and support vector machine , 2011, Neurocomputing.
[57] Mohamad T. Musavi,et al. On the Generalization Ability of Neural Network Classifiers , 1994, IEEE Trans. Pattern Anal. Mach. Intell..
[58] Ratna Babu Chinnam,et al. Support vector machines for recognizing shifts in correlated and other manufacturing processes , 2002 .
[59] J. D. T. Tannock,et al. A neural network approach to characterize pattern parameters in process control charts , 1999, J. Intell. Manuf..