<?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%">Patil, Diwakar</style></author><author><style face="normal" font="default" size="100%">Raj, Rahul</style></author><author><style face="normal" font="default" size="100%">Shingade, Prashant</style></author><author><style face="normal" font="default" size="100%">Kulkarni, Bhaskar</style></author><author><style face="normal" font="default" size="100%">Jayaraman, Valadi K.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Feature selection and classification employing hybrid ant colony optimization/random forest methodology</style></title><secondary-title><style face="normal" font="default" size="100%">Combinatorial Chemistry &amp; High Throughput Screening</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">JUN</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">5</style></number><publisher><style face="normal" font="default" size="100%">BENTHAM SCIENCE PUBL LTD</style></publisher><pub-location><style face="normal" font="default" size="100%">EXECUTIVE STE Y26, PO BOX 7917, SAIF ZONE, 1200 BR SHARJAH, U ARAB EMIRATES</style></pub-location><volume><style face="normal" font="default" size="100%">12</style></volume><pages><style face="normal" font="default" size="100%">507-513</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Accurate classification of instances depends on identification and removal of redundant features. Classification of data having high dimensionality is usually performed in conjunction with an appropriate feature selection method. Feature selection enables identification of the most informative feature subset from the enormously vast search space that can accurately classify the given data. We propose an ant colony optimization (ACO)/random forest based hybrid filter-wrapper search technique, which traverses the search space and selects a feature subset with high classifying ability. We evaluate the performance of our algorithm on four widely studied CoEPrA (Comparative Evaluation of Prediction Algorithms, http://coepra.org) datasets. The performance of the software ants mediated hybrid filter/wrapper approach compares well with the available competition results. Thus, the proposed Ant Colony Optimization based technique can effectively find small feature subsets capable of classifying with a very good accuracy and can be employed for feature subset selection with a high level of confidence.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">5</style></issue><custom3><style face="normal" font="default" size="100%">Foreign</style></custom3><custom4><style face="normal" font="default" size="100%">2.573</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%">Yewalkar-Kulkarni, Swati</style></author><author><style face="normal" font="default" size="100%">Gera, Gayatri</style></author><author><style face="normal" font="default" size="100%">Nene, Sanjay</style></author><author><style face="normal" font="default" size="100%">Pandare, Kiran</style></author><author><style face="normal" font="default" size="100%">Kulkarni, Bhaskar</style></author><author><style face="normal" font="default" size="100%">Kamble, Sanjay</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Exploiting phosphate-starved cells of scenedesmus SP for the treatment of raw sewage</style></title><secondary-title><style face="normal" font="default" size="100%">Indian Journal of Microbiology</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Ankistrodesmus</style></keyword><keyword><style  face="normal" font="default" size="100%">Fourier Transform Infrared</style></keyword><keyword><style  face="normal" font="default" size="100%">Phosphate starvation</style></keyword><keyword><style  face="normal" font="default" size="100%">Scenedesmus</style></keyword><keyword><style  face="normal" font="default" size="100%">Sewage treatment</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2017</style></year><pub-dates><date><style  face="normal" font="default" size="100%">JUN</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">57</style></volume><pages><style face="normal" font="default" size="100%">241-249</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Phosphate depletion is one of the favorable ways to enhance the sewage water treatment with the algae, however, detailed information is essential with respect to internal phosphate concentration and physiology of the algae. The growth rate of the phosphate-starved Scenedesmus cells was reduced drastically after 48 h. Indicating cells entered in the stationary phase of the growth cycle. Fourier Transform Infrared analysis of phosphate-starved Scenedesmus cells showed the reduction in internal phosphate concentration and an increase in carbohydrate/phosphate and carbohydrate/lipid ratio. The phosphate-starved Scenedesmus cells, with an initial cell density of, 1 x 10(6) cells mL(-1) shows 87% phosphate and 100 % nitrogen removal in 24 h. The normal Scenedesmus cells need approximately 48 h to trim down the nutrients from wastewater up to this extent. Other microalgae, Ankistrodesmus, growth pattern was not affected due to phosphate starvation. The cells of Ankistrodesmus was able to reduce 71% phosphate and 73% nitrogen within 24 h, with an initial cell density of, 1 x 10(6) cells mL(-1).&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue><work-type><style face="normal" font="default" size="100%">Article</style></work-type><custom3><style face="normal" font="default" size="100%">Foreign</style></custom3><custom4><style face="normal" font="default" size="100%">1.310</style></custom4></record></records></xml>