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Engineering - Computational Intelligence and Complexity | Machine Learning and Systems Engineering

Machine Learning and Systems Engineering

Ao, Sio-Iong, Rieger, Burghard B., Amouzegar, Mahyar (Eds.)

2010, XXII, 614 p.

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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
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.

Content Level » Research

Keywords » Software - development - entropy - environment - fuzzy - knowledge - learning - machine learning - modeling - multimedia - optimization - robot - simulation - system - systems engineering

Related subjects » Artificial Intelligence - Computational Intelligence and Complexity - Security and Cryptology

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