You are previewing International Journal of Rough Sets and Data Analysis (IJRSDA) Volume 3, Issue 1.
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International Journal of Rough Sets and Data Analysis (IJRSDA) Volume 3, Issue 1

Book Description

The International Journal of Rough Sets and Data Analysis (IJRSDA) is a multidisciplinary journal that publishes high-quality and significant research in all fields of rough sets, granular computing, and data mining techniques. Rough set theory is a mathematical approach concerned with the analysis and modeling of classification and decision problems involving vague, imprecise, uncertain, or incomplete information. Rough sets have been proposed for a variety of applications, including artificial intelligence and cognitive sciences, especially machine learning, knowledge discovery, data mining, expert systems, approximate reasoning, and pattern recognition. The journal extends existing research findings (theoretical innovations and modeling applications) to provide the highest quality original concepts, hybrid applications, innovative methodologies, and development trends studies for all audiences. This journal publishes original articles, reviews, technical reports, patent alerts, and case studies on the latest innovative findings of new methodologies and techniques.

This issue contains the following articles:

  • Hybrid Clustering using Elitist Teaching Learning-Based Optimization: An Improved Hybrid Approach of TLBO
  • Chaotic Map for Securing Digital Content: A Progressive Visual Cryptography Approach
  • Illness Narrative Complexity in Right and Left-Hemisphere Lesions
  • A Rough Set Theory Approach for Rule Generation and Validation Using RSES
  • Information Systems on Hesitant Fuzzy Sets
  • I-Rough Topological Spaces
  • Rough Set Based Similarity Measures for Data Analytics in Spatial Epidemiology

Table of Contents

  1. Cover
  2. Masthead
  3. Call For Articles
  4. Hybrid Clustering using Elitist Teaching Learning-Based Optimization:
    1. ABSTRACT
    2. INTRODUCTION
    3. METHODOLOGY
    4. PROPOSED APPROACH
    5. EXPERIMENTAL SET UP AND RESULT ANALYSIS
    6. CONCLUSION
    7. ACKNOWLEDGMENT
    8. REFERENCES
  5. Chaotic Map for Securing Digital Content:
    1. ABSTRACT
    2. INTRODUCTION
    3. REVIEW OF TRADITIONAL AND PROGRESSIVE VISUAL CRYPTOGRAPHY SCHEMES
    4. CRITICAL ANALYSIS OF HOU&QUAN (2011) PVSS SCHEME
    5. PROPOSED ALGORITHM
    6. CONCLUSION
    7. REFERENCES
  6. Illness Narrative Complexity in Right and Left-Hemisphere Lesions
    1. ABSTRACT
    2. INTRODUCTION
    3. MATERIALS AND METHODS
    4. RESULTS
    5. DISCUSSION
    6. CONCLUSION
    7. REFERENCES
  7. A Rough Set Theory Approach for Rule Generation and Validation Using RSES
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. LITERATURE REVIEW
    4. 3. RULE EXTRACTION PROCESS
    5. 4. RULES VALIDATION USING RSES
    6. 5. CONCLUSION
    7. REFERENCES
  8. Information Systems on Hesitant Fuzzy Sets
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. PRELIMINARIES
    4. 3. HESITANT INFORMATION SYSTEMS
    5. 4. REDUCT AND CORE OF A HESITANT INFORMATION SYSTEM
    6. 5. RELATIVE REDUCT, RELATIVE CORE AND DISCERNIBILITY MATRIX OF A HESITANT DECISION SYSTEM
    7. 6. HOMOMORPHISMS BETWEEN HESITANT FUZZY INFORMATION SYSTEMS
    8. 7. CONCLUSION
    9. REFERENCES
  9. I-Rough Topological Spaces
    1. ABSTRACT
    2. INTRODUCTION
    3. PRELIMINARIES
    4. I-ROUGH TOPOLOGICAL SPACES
    5. I-ROUGH BASE
    6. I-ROUGH SUB-BASE
    7. I-ROUGH SUBSPACES
    8. CONCLUSION
    9. ACKNOWLEDGMENT
    10. REFERENCES
  10. Rough Set Based Similarity Measures for Data Analytics in Spatial Epidemiology
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. BACKGROUND
    4. 3. SPATIAL AUTO-CORRELATION AND DISTRIBUTION OF DISEASE CLUSTERS
    5. 4. ROUGH SETS
    6. 5. CONCLUSION
    7. 6. FUTURE DIRECTIONS
    8. REFERENCES
    9. ADDITIONAL READING
  11. Call For Articles