Nature-Inspired Computation and Machine Learning

Released on by Alexander Gelbukh
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  • Nature-Inspired Computation and Machine Learning Book Detail

  • Author : Alexander Gelbukh
  • Release Date : 2014-11-05
  • Publisher : Springer
  • Genre : Computers
  • Pages : 549
  • ISBN 13 : 331913650X
  • File Size : 76,76 MB
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Nature-Inspired Computation and Machine Learning by Alexander Gelbukh PDF Summary

Book Description: The two-volume set LNAI 8856 and LNAI 8857 constitutes the proceedings of the 13th Mexican International Conference on Artificial Intelligence, MICAI 2014, held in Tuxtla, Mexico, in November 2014. The total of 87 papers plus 1 invited talk presented in these proceedings were carefully reviewed and selected from 348 submissions. The first volume deals with advances in human-inspired computing and its applications. It contains 44 papers structured into seven sections: natural language processing, natural language processing applications, opinion mining, sentiment analysis, and social network applications, computer vision, image processing, logic, reasoning, and multi-agent systems, and intelligent tutoring systems. The second volume deals with advances in nature-inspired computation and machine learning and contains also 44 papers structured into eight sections: genetic and evolutionary algorithms, neural networks, machine learning, machine learning applications to audio and text, data mining, fuzzy logic, robotics, planning, and scheduling, and biomedical applications.

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Nature-Inspired Computing

Nature-Inspired Computing

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Nature-Inspired Computing: Physics and Chemistry-Based Algorithms provides a comprehensive introduction to the methodologies and algorithms in nature-inspired c