Robust soft sensor development using genetic programming

[1]  David L. Elliott,et al.  Neural Systems for Control , 1997 .

[2]  Trevor Hastie,et al.  The Elements of Statistical Learning , 2001 .

[3]  Åsa Jansson,et al.  Development of a software sensor for phosphorus in municipal wastewater , 2002 .

[4]  A. J. Morris,et al.  Solving process engineering problems using artificial neural networks , 1990 .

[5]  Babu Joseph,et al.  Inferential control of processes: Part I. Steady state analysis and design , 1978 .

[6]  A. J. Morris,et al.  Bioprocess model building using artificial neural networks , 1991 .

[7]  Guido Smits,et al.  Hybrid model development methodology for industrial soft sensors , 2003, Proceedings of the 2003 American Control Conference, 2003..

[8]  Alex Arenas,et al.  Neural virtual sensor for the inferential prediction of product quality from process variables , 2002 .

[9]  J. W. Ponton,et al.  Alternatives to neural networks for inferential measurement , 1993 .

[10]  Philip S. Yu,et al.  Outlier detection for high dimensional data , 2001, SIGMOD '01.

[11]  Arthur K. Kordon,et al.  Soft sensor development using genetic programming , 2001 .

[12]  Michael Negnevitsky,et al.  Artificial Intelligence: A Guide to Intelligent Systems , 2001 .

[13]  Gary Montague,et al.  Soft-sensors for process estimation and inferential control , 1991 .

[14]  Amanda J. C. Sharkey,et al.  On Combining Artificial Neural Nets , 1996, Connect. Sci..

[15]  John R. Koza,et al.  Genetic programming - on the programming of computers by means of natural selection , 1993, Complex adaptive systems.

[16]  J. R. Whiteley,et al.  Development of inferential measurements using neural networks. , 2001, ISA transactions.

[17]  Raúl Rojas,et al.  Statistics and Neural Networks , 1996 .

[18]  Richard Weber,et al.  The use of secondary measurements to improve control , 1972 .

[19]  A. Brambilla,et al.  Estimate product quality with ANNs , 1996 .

[20]  Randy J. Pell,et al.  Multiple outlier detection for multivariate calibration using robust statistical techniques , 2000 .

[21]  Gus Eghneim Thoughts on Predictive Emissions Monitoring from a Regulatory Perspective. , 1996, Journal of the Air & Waste Management Association.

[22]  A. J. Morris,et al.  Neural Network Based Estimators for a Batch Polymerization Reactor , 1995 .

[23]  Lahouari Ghouti,et al.  Use of artificial neural networks process analyzers: a case study , 2002, ESANN.

[24]  M. Rao,et al.  Soft sensors for quality prediction in batch chemical pulping processes , 1993, Proceedings of 8th IEEE International Symposium on Intelligent Control.

[25]  Bernhard Schölkopf,et al.  Learning with kernels , 2001 .

[26]  Michael J. Grimble,et al.  Knowledge-based systems for industrial control , 1990 .

[27]  Vladimir Cherkassky,et al.  Learning from Data: Concepts, Theory, and Methods , 1998 .

[28]  Vojislav Kecman,et al.  Learning and Soft Computing: Support Vector Machines, Neural Networks, and Fuzzy Logic Models , 2001 .

[29]  Vladimir Vapnik,et al.  Statistical learning theory , 1998 .

[30]  Barry Lennox,et al.  Industrial application of neural networks — an investigation , 2001 .

[31]  Jules Thibault,et al.  Development of a softsensor for particle size monitoring , 1996 .

[32]  Dong Dong,et al.  Emission monitoring using multivariate soft sensors , 1995, Proceedings of 1995 American Control Conference - ACC'95.

[33]  C. Kiparissides,et al.  Inferential Estimation of Polymer Quality Using Stacked Neural Networks , 1997 .

[34]  Simon Haykin,et al.  Neural Networks: A Comprehensive Foundation , 1998 .

[35]  G. Martin,et al.  Consider soft sensors , 1997 .

[36]  S. Qin,et al.  Self-validating inferential sensors with application to air emission monitoring , 1997 .

[37]  O. A. Sotomayor,et al.  Software sensor for on-line estimation of the microbial activity in activated sludge systems. , 2002, ISA transactions.

[38]  Wolfgang Banzhaf,et al.  Genetic Programming: An Introduction , 1997 .

[39]  Andrei V. Gribok,et al.  Use of Kernel Based Techniques for Sensor Validation in Nuclear Power Plants , 2003 .

[40]  Richard D. Braatz,et al.  Data-driven Methods for Fault Detection and Diagnosis in Chemical Processes , 2000 .