"Artificial Intelligence and Soft Computing, Part I Pt. II" - Information and Links:

Artificial Intelligence and Soft Computing, Part I Pt. II - Info and Reading Options

10th International Conference, ICAISC 2010, Zakopane, Poland, June13-17, 2010, Part I

"Artificial Intelligence and Soft Computing, Part I Pt. II" was published by Springer in 2010 - Berlin, Heidelberg, it has 710 pages and the language of the book is English.


“Artificial Intelligence and Soft Computing, Part I Pt. II” Metadata:

  • Title: ➤  Artificial Intelligence and Soft Computing, Part I Pt. II
  • Authors:
  • Language: English
  • Number of Pages: 710
  • Publisher: Springer
  • Publish Date:
  • Publish Location: Berlin, Heidelberg

Edition Identifiers:

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"Artificial Intelligence and Soft Computing, Part I Pt. II" Description:

Open Data:

Title Page -- Preface -- Organization -- Table of Contents -- Part I Fuzzy Systems and Their Applications -- On the Distributivity of Fuzzy Implications over Continuous Archimedean Triangular Norms -- Introduction -- Basic Notations and Facts -- Eq. (3) When T1, T2 Are Strict -- Eq. (3) When T1, T2 Are Nilpotent -- Eq. (3) When T1 Is Strict and T2 Is Nilpotent -- Eq. (3) When T1 Is Nilpotent and T2 Is Strict -- References -- Fuzzy Decision Support System for Post-Mining Regions Restoration Designing -- Introduction -- Arrangement of Factors Characterizing the Terrain after Exploitation of the Natural Resources -- Fuzzy Rules System -- Applications and Results -- Concluding Remarks -- References -- Fuzzy Digital Filters with Triangular Norms -- Introduction -- Digital Filters with T-Norms -- Digital Filters with Conorms (S-Norms) -- Fuzzy Filters with Triangular Norms -- Conclusion -- References -- A Novel Fuzzy Color Median Filter Based on an Adaptive Cascade of Fuzzy Inference Systems -- Introduction -- Single Input - Single Output Fuzzy Inference Systems for Color Components Ordering -- The Proposed Architecture for Color Filtering in HSV Space -- Implementation and Results -- Conclusions -- References -- Automatic Modeling of Fuzzy Systems Using Particle Swarm Optimization -- Introduction -- Rule Generation Methods -- Proposed Automatic Generation -- Representation -- Particle Position and Movement -- Fitness Function -- Results and Tests -- Conclusion -- References -- On Automatic Design of Neuro-fuzzy Systems -- Introduction -- Description of Flexible Neuro-fuzzy System -- Evolutionary Learning and Designing of Neuro-fuzzy Systems -- Evolution of Parameters of Neuro-fuzzy Systems -- Evolution of Structure of Neuro-fuzzy Systems -- Initialization of the Algorithm -- Fitness Function -- Experimental Results -- Summary -- References

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