<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kumar, R.</style></author><author><style face="normal" font="default" size="100%">Jayaraman, Valadi K.</style></author><author><style face="normal" font="default" size="100%">Kulkarni, B. D.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">SVM classifier incorporating simultaneous noise reduction and feature selection: illustrative case examples</style></title><secondary-title><style face="normal" font="default" size="100%">Pattern Recognition</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">classification</style></keyword><keyword><style  face="normal" font="default" size="100%">conditional entropy</style></keyword><keyword><style  face="normal" font="default" size="100%">SVM</style></keyword><keyword><style  face="normal" font="default" size="100%">symbolization</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2005</style></year><pub-dates><date><style  face="normal" font="default" size="100%">JAN</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">1</style></number><publisher><style face="normal" font="default" size="100%">PERGAMON-ELSEVIER SCIENCE LTD</style></publisher><pub-location><style face="normal" font="default" size="100%">THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND</style></pub-location><volume><style face="normal" font="default" size="100%">38</style></volume><pages><style face="normal" font="default" size="100%">41-49</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;A hybrid technique involving symbolization of data to remove noise and use of conditional entropy minima to extract relevant and non-redundant features is proposed in conjunction with support vector machines to obtain more robust classification algorithm. The technique tested on three data sets shows improvements in classification efficiencies. (C) 2004 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><work-type><style face="normal" font="default" size="100%">Article</style></work-type><custom3><style face="normal" font="default" size="100%">&lt;p&gt;Foreign&lt;/p&gt;</style></custom3><custom4><style face="normal" font="default" size="100%">3.399</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gandhi, Ankit B.</style></author><author><style face="normal" font="default" size="100%">Joshi, J. B.</style></author><author><style face="normal" font="default" size="100%">Kulkarni, A. A.</style></author><author><style face="normal" font="default" size="100%">Jayaraman, Valadi K.</style></author><author><style face="normal" font="default" size="100%">Kulkarni, B. D.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">SVR-based prediction of point gas hold-up for bubble column reactor through recurrence quantification analysis of LDA time-series</style></title><secondary-title><style face="normal" font="default" size="100%">International Journal of Multiphase Flow</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Bubble column</style></keyword><keyword><style  face="normal" font="default" size="100%">Gas hold-up</style></keyword><keyword><style  face="normal" font="default" size="100%">LDA</style></keyword><keyword><style  face="normal" font="default" size="100%">Recurrence quantification analysis (RQA)</style></keyword><keyword><style  face="normal" font="default" size="100%">Support vector regression (SVR)</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">DEC</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">12</style></number><publisher><style face="normal" font="default" size="100%">PERGAMON-ELSEVIER SCIENCE LTD</style></publisher><pub-location><style face="normal" font="default" size="100%">THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND</style></pub-location><volume><style face="normal" font="default" size="100%">34</style></volume><pages><style face="normal" font="default" size="100%">1099-1107</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Recurrence quantification analysis (RQA) has emerged as a useful tool for detecting singularities in nonstationary time-series data. In this paper, we use RQA to analyze the velocity-time data acquired using laser doppler anemometry (LDA) signals in a bubble column reactor for Single point and Multipoint point spargers. The recurring dynamical states within the velocity-time-series occurring due to the bubble and the liquid passage at the point of measurement, are quantified by RQA features (namely % Recurrence, % Determinism, % Laminarity and Entropy), which in turn are regressed using support vector regression (SVR) to predict the point gas hold-up values. It has been shown that SVR-based model for the bubble column reactor can be potentially useful for online prediction and monitoring of the point gas hold-up for different sparging conditions. (C) 2008 Elsevier Ltd. All rights reserved.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">12</style></issue><custom3><style face="normal" font="default" size="100%">Foreign</style></custom3><custom4><style face="normal" font="default" size="100%">1.772</style></custom4></record></records></xml>