<?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%">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>