Intuitionistic Fuzziness and Other Intelligent Theories and Their Applications (Studies in Computational Intelligence) (2019)

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Intuitionistic Fuzziness and Other Intelligent Theories and Their Applications (Studies in Computational Intelligence) (2019)

  • オンデマンド(OD/POD)版です。キャンセルは承れません。
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  • 製本 Hardcover:ハードカバー版/ページ数 193 p.
  • 言語 ENG
  • 商品コード 9783319789309
  • DDC分類 006.3

Full Description

This book gathers extended versions of the best papers presented at the 8th IEEE conference on Intelligent Systems, held in Sofia, Bulgaria on September 4-6, 2016, which are mainly related to theoretical research in the area of intelligent systems. The main focus is on novel developments in fuzzy and intuitionistic fuzzy sets, the mathematical modelling tool of generalized nets and the newly defined method of intercriteria analysis. The papers reflect a broad and diverse team of authors, including many young researchers from Australia, Bulgaria, China, the Czech Republic, Iran, Mexico, Poland, Portugal, Slovakia, South Korea and the UK.

Contents

Intercriteria Analysis and Arithmetic Functions.- Fuzzy Harmony Search Algorithm Using an Interval type- 2 Fuzzy Logic Applied to Benchmark Mathematical Functions.- Mixture Initialization Based on Prior Data Visual Analysis.- Spatiotemporal Parameter Estimation of Thermal Treatment Process via Initial Condition Reconstruction Using Neural Networks.- Interval type-2 Fuzzy Logic Dynamic Mutation and Cross-over Parameter Adaptation in a Fuzzy Differential Evolution Method.- Intuitionistic Fuzzy Evaluations for the Analysis of a Student's Knowledge in University e-Learning Courses.- S-logic with first and second imaginary states.- Generalized Net Model of the Processes in a Center of Transfusion Haematology.- Image to Sound Encryption Using a Self-Organizing Map Neural Network.- On Different Algorithms for InterCriteria Relations Calculation.- Defining Consonance Thresholds in InterCriteria Analysis: An Overview.- Design and Comparison of ECG Arrhythmias Classifiers Using Discrete Wavelet Transform, Neural Network and Principal Component Analysis.

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