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Applying Computational Intelligence for Social Good. Track, Understand and Build a Better world. Advances in Computers Volume 132

  • Book

  • January 2024
  • Region: Global
  • Elsevier Science and Technology
  • ID: 5894662

Applying Computational Intelligence for Social Good: Track, Understand and Build a Better World, Volume 132 presents views on how Computational Intelligent and ICT technologies can be applied to ease or solve social problems by sharing examples of research results from studies of social anxiety, environmental issues, mobility of the disabled, and problems in social safety. Sample chapters in this release include Why is implementing Computational Intelligence for social good so challenging? Principles and its Application, Smart crisis management system for road accidents using Geo-Spacial Machine Learning Techniques, Residential Energy Management System (REMS) Using Machine Learning, Text-Based Personality Prediction using XLNet, and much more.

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Table of Contents

1. Why is implementing Computational Intelligence for social good so challenging? Principles and its Application Preetha Evangeline and Anandhakumar P 2. Smart crisis management system for road accidents using Geo-Spacial Machine Learning Techniques Cephas Paul Edward 3. Residential Energy Management System (REMS) Using Machine Learning G Ramya and R Ramaprabha 4. Text-Based Personality Prediction using XLNet Ashok Kumar Jayaraman and Gayathri Ananthakrishnan 5. Articulating the power of reasoning and gathering data for Information security and Justice Preetha Evangeline and Anandhakumar P 6. Blockchain Smart Contracts Quality Measurement using Bayesian Networks Lakshminarayana Kodavali I and K. Sathiyamurthy 7. Short-Term Wind Power Prediction Using Deep Learning Approaches Anandhakumar P and Alex Luke K.A 8. Cyber Data Trend and Intelligent Computing Atma Sahu and Preetha Evangeline 9. Demystifying the Edge Intelligence Pethuru Raj Chelliah Sr. and Preetha Evangeline 10. An Automatic Path Navigation for Visually Challenged People using Deep Q Learning Muthurajkumar S 11. Delineating Computational Intelligence during Epidemic Emergencies and Outbreaks Preetha Evangeline and V. Vivek 12. Deep Learning Model for Computation, Calibration and Estimation of Biotic Stress in Crops Preetha Evangeline and Anandhakumar P 13. Weather Nowcasting Model: A Rough Set Approach S. Anbarasu and Anandhakumar P 14. Intelligent methodologies for Assessment of Plant exracts as protectants against storage pests Gowthamy U. and Hemalatha G. 15. Automatic programming (source code generator) based on an ontological model Preetha Evangeline and Rex Vinod. A