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Tang, W., Liu, Q., Wang, M., Zong, D.: Method and Implementation of Soft Measurement On-line to the Baume Degree of Black Liquor. Chemical Industry Automation and Instrumentation 32(2), 47–50 (2005)
Vapnik, V.N.: The Nature of Statistical Learning Theory. Springer, New York (1999)
Li, F., Zhao, Y., Jiang, Z.: The prediction of oil quality based on least squares support vector machines and dau2bechies wavelet and mallat algorithm. In: Proceedings of the Sixth International Conference on Intelligent Systems Design and Applications (2006)
Zhang, M., Li, Z., Li, W.: Study on least squares support vector machines algorithm and its application. Science press, Beijing (2004)
Yan, W., Shao, H.: Application of support vector machines and least squares support vector machines to heart disease diagnoses. Control and Decision 18(3), 358–360 (2003)
Vapnik, V.N.: An overview of statistical learning theory. IEEE Trans. Neural Network 10(5), 988–999 (1999)
Zhang, L., Zhou, W., Jiao, L.: Wavelet support vector machine. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 34(1), 34–39 (2003)
Lin, C.-J.: Formulations of support vector machines:A note from an optimization point of view. Neural Computation 13(2), 307–317 (2001)
Varma, A., Jacobson, Q.: Destage Algorithms for Disk Arrays with Nonvolatile Caches. IEEE Trans. on Computers 47(2), 228–235 (1998)
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© 2012 Springer-Verlag GmbH Berlin Heidelberg
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Zhang, G., Li, X. (2012). A New Online Soft Measurement Method for Baume Degrees of Black Liquor. In: Jin, D., Lin, S. (eds) Advances in Future Computer and Control Systems. Advances in Intelligent and Soft Computing, vol 159. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29387-0_55
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DOI: https://doi.org/10.1007/978-3-642-29387-0_55
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-29386-3
Online ISBN: 978-3-642-29387-0
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