Overview

A large international conference on Advances in Machine Learning and Data Analysis was held in UC Berkeley, California, USA, October 22-24, 2008, under the auspices of the World Congress on Engineering and Computer Science (WCECS 2008). This volume contains sixteen revised and extended research articles written by prominent researchers participating in the conference. Topics covered include Expert system, Intelligent decision making, Knowledge-based systems, Knowledge extraction, Data analysis tools, Computational biology, Optimization algorithms, Experiment designs, Complex system identification, Computational modeling, and industrial applications. Advances in Machine Learning and Data Analysis offers the state of the art of tremendous advances in machine learning and data analysis and also serves as an excellent reference text for researchers and graduate students, working on machine learning and data analysis.

Full Product Details

Author:   Mahyar Amouzegar ,  Burghard B. Rieger ,  Mahyar Amouzegar
Publisher:   Springer
Imprint:   Springer
Edition:   2010 ed.
Volume:   48
Dimensions:   Width: 15.50cm , Height: 1.50cm , Length: 23.50cm
Weight:   1.160kg
ISBN:  

9789048131761

ISBN 10:   9048131766
Pages:   239
Publication Date:   23 November 2009
Audience:   College/higher education ,  Professional and scholarly ,  Postgraduate, Research & Scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print  
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Table of Contents

1 2D/3D Image Data Analysis for Object Tracking and Classification; Seyed Eghbal Ghobadi, Omar Edmond Loepprich, Oliver Lottner, Klaus Hartmann, Wolfgang Weihs, Otmar Loffeld. 2 Robot Competence Development by Constructive Learning ; Q. Meng, M.H. Lee, C.J. Hinde. 3 Using DigitalWatermarking for Securing Next Generation Media Broadcasts; Dominik Birk, Seán Gaines. 4 A Reduced-Dimension ProcessorModel; Azam Beg. 5 Hybrid Machine Learning Model for Continuous Microarray Time Series; S.-I. Ao. 6 An Asymptotic Method to a Financial Optimization Problem; Dejun Xie, David Edwards, Giberto Schleiniger. 7 Analytical Design of Robust Multi-loop PI Controller for Multi-time Delay Processes; Truong Nguyen Luan Vu, Moonyong Lee. 8 Automatic and Semi-automaticMethods for the Detection of Quasars in Sky Surveys; S.-I. Ao. 9 Improving Low-Cost Sail Simulator Results by Artificial Neural Networks Models; V. Díaz Casás, P. Porca Belío, F. López Peña, R.J. Duro. 10 Rough Set Approaches to Unsupervised Neural Network Based Pattern Classifier; Ashwin Kothari, Avinash Keskar. 11 A New Robust Combined Method for Auto Exposure and Auto White-Balance; Quoc Kien Vuong, Se-Hwan Yun, Suki Kim. 12 A Mathematical Analysis Around Capacitive Characteristics of the Current of CSCT: Optimum Utilization of Capacitors of Harmonic Filters; Mohammad Golkhah, Mohammad Tavakoli Bina. 13 Harmonic Analysis and Optimum Allocation of Filters in CSCT; Mohammad Golkhah, Mohammad Tavakoli Bina. 14 Digital Pen and Paper Technology as a Means of Classroom Administration Relief; Jan Broer, Tim Wendisch, Nina Willms. 15 A Conceptual Model for a Network-Based Assessment Security System; Nathan Percival, Jennifer Percival, Clemens Martin. 16 IncorrectWeighting of Absolute Performance in Self-Assessment; Scott A. Jeffrey, Brian Cozzarin.

Reviews

From the reviews: This is a collection of papers from a large international conference on advances in machine learning and data analysis ! . Readers who work with digital systems ! would benefit most from this book. ! Each chapter has ! a bibliography that helps readers find further references, when needed. ! the topics covered in this book should be of great interest to researchers and practitioners who want to apply machine learning technology and data analysis tools to problems in general electrical engineering areas ! . (Xiannong Meng, ACM Computing Reviews, March, 2010)

From the reviews: “This is a collection of papers from a large international conference on advances in machine learning and data analysis … . Readers who work with digital systems … would benefit most from this book. … Each chapter has … a bibliography that helps readers find further references, when needed. … the topics covered in this book should be of great interest to researchers and practitioners who want to apply machine learning technology and data analysis tools to problems in general electrical engineering areas … .” (Xiannong Meng, ACM Computing Reviews, March, 2010)

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