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Machine Learning and Systems Engineering

  • Book
  • © 2010

Overview

Editors:
  1. Sio-Iong Ao

    1. , Unit 1, 1/F, International Association of Engineers, Hong Kong, Hong Kong/PR China

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  2. Burghard Rieger

    1. Inst.Computerlinguistik, Abt. Linguistische Datenverarbeitung, Universität Trier, Trier, Germany

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  3. Mahyar A. Amouzegar

    1. Dept. Chemical Engineering, California State University, Long Beach, USA

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  • Offers the state of the art of tremendous advances in machine learning and systems engineering
  • Serves as an excellent reference text for researchers and graduate students, working on machine learning and systems engineering
  • Contains forty-six revised and extended research articles written by prominent researchers
  • Includes supplementary material: sn.pub/extras

Part of the book series: Lecture Notes in Electrical Engineering (LNEE, volume 68)

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Table of contents (46 chapters)

  1. Front Matter

    Pages i-xxii
    Download chapter PDF

  2. Multimodal Human Spacecraft Interaction in Remote Environments

    • Enrico Stoll, Alvar Saenz-Otero, Brent Tweddle
    Pages 1-15

  3. A Framework for Collaborative Aspects of Intelligent Service Robot

    • Joohee Suh, Chong-woo Woo
    Pages 17-29

  4. Piecewise Bezier Curves Path Planning with Continuous Curvature Constraint for Autonomous Driving

    • Ji-Wung Choi, Renwick Curry, Gabriel Elkaim
    Pages 31-45

  5. Combined Heuristic Approach to Resource-Constrained Project Scheduling Problem

    • Miloš Šeda, Radomil Matoušek, Pavel Ošmera, Čeněk Šandera, Roman Weisser
    Pages 47-57

  6. A Development of Data-Logger for Indoor Environment

    • Anuj Kumar, I. P. Singh, S. K. Sud
    Pages 59-69

  7. Multiobjective Evolutionary Optimization and Machine Learning: Application to Renewable Energy Predictions

    • Kashif Gill, Abedalrazq Khalil, Yasir Kaheil, Dennis Moon
    Pages 71-82

  8. Hybriding Intelligent Host-Based and Network-Based Stepping Stone Detections

    • Mohd Nizam Omar, Rahmat Budiarto
    Pages 83-95

  9. Open Source Software Use in City Government

    • David J. Ward, Eric Y. Tao
    Pages 97-109

  10. Pheromone-Balance Driven Ant Colony Optimization with Greedy Mechanism

    • Masaya Yoshikawa
    Pages 111-119

  11. Study of Pitchfork Bifurcation in Discrete Hopfield Neural Network

    • R. Marichal, J. D. Piñeiro, E. González, J. Torres
    Pages 121-130

  12. Grammatical Evolution and STE Criterion

    • Radomil Matousek, Josef Bednar
    Pages 131-142

  13. Data Quality in ANFIS Based Soft Sensors

    • S. Jassar, Z. Liao, L. Zhao
    Pages 143-155

  14. The Meccano Method for Automatic Volume Parametrization of Solids

    • R. Montenegro, J. M. Cascón, J. M. Escobar, E. Rodríguez, G. Montero
    Pages 157-167

  15. A Buck Converter Model for Multi-Domain Simulations

    • Johannes V. Gragger, Anton Haumer, Markus Einhorn
    Pages 169-181

  16. The Computer Simulation of Shaping in Rotating Electrical Discharge Machining

    • Jerzy Kozak, Zbigniew GulbinowiczGulbinowicz
    Pages 183-195

  17. Parameter Identification of a Nonlinear Two Mass System Using Prior Knowledge

    • C. Endisch, M. Brache, R. Kennel
    Pages 197-211

  18. Adaptive and Neural Learning for Biped Robot Actuator Control

    • Pavan K. Vempaty, Ka C. Cheok, Robert N. K. Loh, Micho Radovnikovich
    Pages 213-225

  19. Modeling, Simulation, and Analysis for Battery Electric Vehicles

    • Wei Zhan, Make McDermott, Behbood Zoghi, Muhammad Hasan
    Pages 227-241

  20. Modeling Confined Jets with Particles and Swril

    • Osama A. Marzouk, E. David Huckaby
    Pages 243-256
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Keywords

About this book

A large international conference on Advances in Machine Learning and Systems Engineering was held in UC Berkeley, California, USA, October 20-22, 2009, under the auspices of the World Congress on Engineering and Computer Science (WCECS 2009). Machine Learning and Systems Engineering contains forty-six 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. Machine Learning and Systems Engineering offers the state of the art of tremendous advances in machine learning and systems engineering and also serves as an excellent reference text for researchers and graduate students, working on machine learning and systems engineering.

Editors and Affiliations

  • , Unit 1, 1/F, International Association of Engineers, Hong Kong, Hong Kong/PR China

    Sio-Iong Ao

  • Inst.Computerlinguistik, Abt. Linguistische Datenverarbeitung, Universität Trier, Trier, Germany

    Burghard Rieger

  • Dept. Chemical Engineering, California State University, Long Beach, USA

    Mahyar A. Amouzegar

Bibliographic Information

  • Book Title: Machine Learning and Systems Engineering

  • Editors: Sio-Iong Ao, Burghard Rieger, Mahyar A. Amouzegar

  • Series Title: Lecture Notes in Electrical Engineering

  • DOI: https://doi.org/10.1007/978-90-481-9419-3

  • Publisher: Springer Dordrecht

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer Science+Business Media B.V. 2010

  • Hardcover ISBN: 978-90-481-9418-6Published: 09 October 2010

  • Softcover ISBN: 978-94-007-3374-9Published: 05 December 2012

  • eBook ISBN: 978-90-481-9419-3Published: 05 October 2010

  • Series ISSN: 1876-1100

  • Series E-ISSN: 1876-1119

  • Edition Number: 1

  • Number of Pages: XXII, 614

  • Topics: Computational Intelligence, Artificial Intelligence, Systems and Data Security

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