Fuzzy Intelligent Systems
Chandrasekaran, E., Anandan, R., Suseendran, G., Balamurugan, S. Appavu Alias 1985-, Hachimi, Hanaa · 2021
Intro - Title Page - Copyright - Preface - 1 Fuzzy Fractals in Cervical Cancer - 1.1 Introduction - 1.2 Methods - 1.3 Maximum Modulus Theorem - 1.4 Results - 1.5 Conclusion - References - 2 Emotion Detection in IoT-Based E-Learning Using Convolution Neural Network - 2.1 Introduction - 2.2 Related Works - 2.3 Proposed Methodology - 2.4 Experimental Results - 2.5 Conclusions - References - 3 Fuzzy Quotient-3 Cordial Labeling of Some Trees of Diameter 5-Part III - 3.1 Introduction - 3.2 Related Work - 3.3 Definition - 3.4 Notations - 3.5 Main Results - 3.6 Conclusion - References - 4 Classifying Fuzzy Multi-Criterion Decision Making and Evolutionary Algorithm - 4.1 Introduction - 4.2 Multiple Criteria That is Used for Decision Making (MCDM) - 4.3 Conclusion - References - 5 Fuzzy Tri-Magic Labeling of Isomorphic Caterpillar Graph of Diameter 5 - 5.1 Introduction - 5.2 Main Result - 5.3 Conclusion - References - 6 Fuzzy Tri-Magic Labeling of Isomorphic Caterpillar Graph of Diameter 5 - 6.1 Introduction - 6.2 Main Result - 6.3 Conclusion - References - 7 Ceaseless Rule-Based Learning Methodology for Genetic Fuzzy Rule-Based Systems - 7.1 Introduction - 7.2 Existing Technology and its Review - 7.3 Research Design - 7.4 Findings or Result Discussion so for in the Area of GFS Hybridization - 7.5 Conclusion - References - 8 Using Fuzzy Technique Management of Configuration and Status of VM for Task Distribution in Cloud System - 8.1 Introduction - 8.2 Literature Review - 8.3 Logic System for Fuzzy - 8.4 Proposed Algorithm - 8.5 Results of Simulation - 8.6 Conclusion - References - 9 Theorems on Fuzzy Soft Metric Spaces - 9.1 Introduction - 9.2 Preliminaries - 9.3 FSMS - 9.4 Main Results - 9.5 Fuzzy Soft -Contractive Type Mappings and - Admissible Mappings - References.