Alexey N. Averkin, Dmitry I. Ignatov, Sushmita Mitra, Jonas Poelmans, Valery B. Tarasov (Eds.)
Volume Editors
Copyright c 2011 for the individual papers by papers' authors, for the Volume by the editors. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means without the prior permission of the copyright owners. Soft computing is a collection of methodologies, which aim to exploit tolerance for imprecision, uncertainty and partial truth to achieve tractability, robustness and low cost solution in real life tasks. This volume contains the papers presented at SCAKD-2011: The International Workshop on Soft Computing Applications and Knowledge Discovery held on June 25, 2011 in Moscow. This workshop was initiated with the aim of presenting high quality scienti c results and promising research in the areas of soft computing and data mining, particularly by young researchers, with an objective of bringing them to the focus while promoting collaborative research activities. The main goal of this workshop was to gather researchers all areas of Soft Computing Applications and Knowledge Discovery, including but not limited to the following: Pattern Recognition, Data Mining & Knowledge Discovery, Fuzzy & Neural Networks, Evolutionary & Probabilistic Computing, Swarm Intelligence, Collective Intelligence, Machine Learning, Information Retrieval, Rough Sets, Soft Computing, Bio-informatics, Biometrics, Computational Biology, Clustering, Formal Concept Analysis, Ontology Learning, Decision Support Systems & Business Intelligence (OLAP and BI, Data Warehouse Modeling, ETL techniques and technologies, and Data Visualization), Recommender Systems, Modeling of user behavior, and Applications of Soft Computing.
By holding the workshop in conjunction with PReMI and RSFDGrC, we hope to provide the contributers exposure and interaction with eminent scientists, engineers, professionals, and researchers in related elds. We are proud that in total, 15 papers were accepted for oral presentation and publication in the proceedings. Finally we would like to say a word of thank to the administration of the Higher School of Economics who took care of all arrangements to make this conference pleasant and enjoyable.
June, 2011 Moscow
Dmitry I. Ignatov
Sushmita Mitra
Jonas Poelmans
Valery B. Tarasov
Organization This SCAKD'11 workshop was held in June 2011 in Moscow, Russia co-located with the 13th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing (RSFDGrC-2011) and 4th International Conference on Pattern Recognition and Machine Intelligence (PReMI-2011) at the National Research University Higher School of Economics.
ABBYY, Moscow Russian Foundation for Basic Research, Moscow Poncelet Laboratory (UMI 2615 du CNRS), Moscow State University Higher School of Economics, Moscow Yandex, Moscow Witology, Moscow Dynasty Foundation, Moscow
Dmitry I. Ignatov Sushmita Mitra Jonas Poelmans Valery B. Tarasov
Mehdi Kaytoue, France Yuri Kudryavtsev, Russia Sergei Kuznetsov, Russia Xenia Naidenova, Russia Andrey Savchenko, Russia Dominik Slezak, Poland Laszlo Szathmary, Canada Rustam Tagiew, Germany
Dorodnicyn Computing Centre of the Russian Academy of Sciences, Russia State University Higher School of Economics, Russia Indian Statistical Institute, India Katholieke Universiteit Leuven, Belgium
Bauman Moscow State Technical University, Russia Forecasting the U.S. stock market via Levenberg-Marquardt and Herman Haken arti cial neural networks using ICA&PCA pre-processing techniques : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : :
Sergey Golovachev Estimating Probability of Failure of a Complex System Based on Partial Information about Subsystems and Components, with Potential Applications to Aircraft Maintenance : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : Christelle Jacob, Didier Dubois, Janette Cardoso, Martine Ceberio and Vladik Kreinovich Stepwise Feature Selection Using Multiple Kernel Learning : : : : : : : : : : : : :
Vilen Jumutc Empirical reconstruction of fuzzy model of experiment in the Euclidean metric : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : :
Tatiana Kopit SVM Based O ine Handwritten Gurmukhi Character Recognition : : : : : :
Munish Kumar, M. K. Jindal and R. K. Sharma Obtaining of a Minimal Polygonal Representation of a Curve by Means of a Fuzzy Clustering : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : :
Alexander Lepskiy KDDClus: A Simple Method for Multi-Density Clustering : : : : : : : : : : : : : :
Sushmita Mitra and Jay Nandy Intelligent Data Mining for Turbo-Generator Predictive Maintenance: An Approach in Real-World : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : Alexandre Pellicel, Goncalo Cassio, Marco Aurelio Lopes, Luiz Eduardo Borges Da Silva, Erik Bonaldi, Levy Ely Lacerda De Oliveira, Jonas Borges Da Silva, Germano Lambert-Torres and Pierre Rodrigues Fuzzy Predicting Models in "Structure - Property" Problem : : : : : : : : : : : : Eugeny Prokhorov, Ludmila Ponomareva, Eugeny Permyakov and Mikhail Kumskov 1 12 23 30 42 48 51 63 72 77 89 Construction of Enzyme Network of Arabidopsis thaliana using graph theory : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 125 Kasthuribai Viswanathan and Nita Parekh