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There are 3730 results for: content related to: Application of support vector regression for developing soft sensors for nonlinear processes

  1. Novel soft sensor modeling and process optimization technique for commercial petrochemical plant

    Asia-Pacific Journal of Chemical Engineering

    Volume 5, Issue 5, September/October 2010, Pages: 721–731, S. K. Lahiri and Nadeem M. Khalfe

    Article first published online : 20 OCT 2009, DOI: 10.1002/apj.399

  2. You have free access to this content
    Soft sensors in bioprocessing: A status report and recommendations

    Biotechnology Journal

    Volume 7, Issue 8, August 2012, Pages: 1040–1048, Reiner Luttmann, Daniel G. Bracewell, Gesine Cornelissen, Krist V. Gernaey, Jarka Glassey, Volker C. Hass, Christian Kaiser, Christian Preusse, Gerald Striedner and Prof. Carl-Fredrik Mandenius

    Article first published online : 5 APR 2012, DOI: 10.1002/biot.201100506

  3. Industrial melt index prediction with the ensemble anti-outlier just-in-time Gaussian process regression modeling method

    Journal of Applied Polymer Science

    Volume 132, Issue 22, June 10, 2015, Yi Liu and Zengliang Gao

    Article first published online : 10 FEB 2015, DOI: 10.1002/app.41958

  4. Mini-review: soft sensors as means for PAT in the manufacture of bio-therapeutics

    Journal of Chemical Technology and Biotechnology

    Volume 90, Issue 2, February 2015, Pages: 215–227, Carl-Fredrik Mandenius and Robert Gustavsson

    Article first published online : 1 AUG 2014, DOI: 10.1002/jctb.4477

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    Unified correlation for overall gas hold-up in bubble column reactors for various gas–liquid systems using hybrid genetic algorithm-support vector regression technique

    The Canadian Journal of Chemical Engineering

    Volume 88, Issue 5, October 2010, Pages: 758–776, Ankit B. Gandhi and Jyeshtharaj B. Joshi

    Article first published online : 30 JUN 2010, DOI: 10.1002/cjce.20296

  6. Semisupervised Bayesian method for soft sensor modeling with unlabeled data samples

    AIChE Journal

    Volume 57, Issue 8, August 2011, Pages: 2109–2119, Zhiqiang Ge and Zhihuan Song

    Article first published online : 20 OCT 2010, DOI: 10.1002/aic.12422

  7. Nonlinear semisupervised principal component regression for soft sensor modeling and its mixture form

    Journal of Chemometrics

    Volume 28, Issue 11, November 2014, Pages: 793–804, Zhiqiang Ge, Biao Huang and Zhihuan Song

    Article first published online : 4 JUN 2014, DOI: 10.1002/cem.2638

  8. Soft sensor development for nonlinear and time-varying processes based on supervised ensemble learning with improved process state partition

    Asia-Pacific Journal of Chemical Engineering

    Volume 10, Issue 2, March/April 2015, Pages: 282–296, Weiming Shao, Xuemin Tian and Ping Wang

    Article first published online : 8 MAR 2015, DOI: 10.1002/apj.1874

  9. Application of online support vector regression for soft sensors

    AIChE Journal

    Volume 60, Issue 2, February 2014, Pages: 600–612, Hiromasa Kaneko and Kimito Funatsu

    Article first published online : 19 DEC 2013, DOI: 10.1002/aic.14299

  10. Probabilistic slow feature analysis-based representation learning from massive process data for soft sensor modeling

    AIChE Journal

    Chao Shang, Biao Huang, Fan Yang and Dexian Huang

    Article first published online : 18 JUL 2015, DOI: 10.1002/aic.14937

  11. Process modeling and optimization of industrial ethylene oxide reactor by integrating support vector regression and genetic algorithm

    The Canadian Journal of Chemical Engineering

    Volume 87, Issue 1, February 2009, Pages: 118–128, Sandip Kumar Lahiri and Nadeem Khalfe

    Article first published online : 25 FEB 2009, DOI: 10.1002/cjce.20123

  12. Intrinsic fluorescence-based at situ soft sensor for monitoring monoclonal antibody aggregation

    Biotechnology Progress

    Kaveh Ohadi, Raymond L. Legge and Hector M. Budman

    Article first published online : 22 JUL 2015, DOI: 10.1002/btpr.2140

  13. Soft Sensor Based on Relevance Vector Machines for Microbiological Fermentation

    Developments in Chemical Engineering and Mineral Processing

    Volume 13, Issue 3-4, 2005, Pages: 243–248, Zonghai Sun and Youxian Sun

    Article first published online : 15 MAY 2008, DOI: 10.1002/apj.5500130305

  14. Soft sensor solutions for control of oil sands processes

    The Canadian Journal of Chemical Engineering

    Volume 91, Issue 8, August 2013, Pages: 1416–1426, Shima Khatibisepehr, Biao Huang, Elom Domlan, Elham Naghoosi, Yu Zhao, Yu Miao, Xinguang Shao, Swanand Khare, Marziyeh Keshavarz, Enbo Feng, Fangwei Xu, Aris Espejo and Ramesh Kadali

    Article first published online : 26 APR 2013, DOI: 10.1002/cjce.21833

  15. A soft sensor for flotation plants

    The Canadian Journal of Chemical Engineering

    Volume 76, Issue 1, February 1998, Pages: 156–160, Claude Bazin and Andrew Trusiak

    Article first published online : 27 MAR 2009, DOI: 10.1002/cjce.5450760121

  16. Support Vector Machines for 3D Shape Processing

    Computer Graphics Forum

    Volume 24, Issue 3, September 2005, Pages: 285–294, Florian Steinke, Bernhard Schölkopf and Volker Blanz

    Article first published online : 7 OCT 2005, DOI: 10.1111/j.1467-8659.2005.00853.x

  17. Support vector machines in engineering: an overview

    Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery

    Volume 4, Issue 3, May/June 2014, Pages: 234–267, S. Salcedo-Sanz, J. L. Rojo-Álvarez, M. Martínez-Ramón and G. Camps-Valls

    Article first published online : 28 APR 2014, DOI: 10.1002/widm.1125

  18. Left-inversion soft-sensor of synchronous generator

    International Transactions on Electrical Energy Systems

    Volume 23, Issue 1, January 2013, Pages: 48–61, Kaifeng Zhang, Xianzhong Dai and Chongxin Huang

    Article first published online : 13 OCT 2011, DOI: 10.1002/etep.642

  19. Sensor systems for bioprocess monitoring

    Engineering in Life Sciences

    Volume 15, Issue 5, July 2015, Pages: 469–488, Philipp Biechele, Christoph Busse, Dörte Solle, Thomas Scheper and Kenneth Reardon

    Article first published online : 12 MAY 2015, DOI: 10.1002/elsc.201500014

  20. Observability analysis of biochemical process models as a valuable tool for the development of mechanistic softsensors

    Biotechnology Progress

    Accepted manuscript online: 24 SEP 2015, Aydin Golabgir, Thomas Hoch, Mariya Zhariy and Christoph Herwig

    DOI: 10.1002/btpr.2176