Skip to main content
View Cart

Applying Computational Intelligence for Social Good

Track, Understand and Build a Better world

  • 1st Edition, Volume 132 - January 14, 2024
  • Latest edition
  • Editors: Preetha Evangeline David, P Anandhakumar
  • Language: English

Applying Computational Intelligence for Social Good: Track, Understand and Build a Better World, Volume 132 presents views on how Computational Intelligent and ICT technolog… Read more

Early spring sale

Nurture your knowledge

Grow your expertise with up to 25% off trusted resources.

Shop now

Description

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.

Key features

  • Explores a number of key themes, including self-organization, complex adaptive systems, and emergent computation for solving socially relevant problems
  • Focuses on Forecasting applications, Human Behavior and Critics response analysis in social forums, Healthcare monitoring Systems, Disaster Management, Industrial management, and most recently, Epidemics and Outbreaks
  • Brings together many different aspects of the current research on intelligence technologies, such as neural networks, support vector machines, fuzzy logic, and evolutionary computation

Readership

Researchers from Industries, Academicians, carrying out transdisciplinary research and working in the field of Epidemics and outbreaks, Healthcare monitoring, Smart Agriculture, IoT, Intelligent Systems etc. ICTs Academicians and UG/PG Computer science students involved in doing projects in the fields of Data Science, Internet of Things and Artificial Intelligence and Machine and Deep Learning. Cloud/Edge/Fog and IoT Architects. Artificial Intelligence experts

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

Product details

  • Edition: 1
  • Latest edition
  • Volume: 132
  • Published: January 14, 2024
  • Language: English

About the editors

PD

Preetha Evangeline David

Dr. Preetha Evangeline David is currently working as an Associate Professor and Head of the Department in the Department of Artificial Intelligence and Machine Learning at Chennai Institute of Technology, Chennai, India. She holds a PhD from Anna University, Chennai in the area of Cloud Computing. She has published many research papers and Patents focusing on Artificial Intelligence, Digital Twin Technology, High Performance Computing, Computational Intelligence and Data Structures. She is currently working on Multi-disciplinary areas in collaboration with other technologies to solve socially relevant challenges and provide solutions to human problems.
Affiliations and expertise
Associate Professor and Head of the Department in the Department of Artificial Intelligence and Machine Learning at Chennai Institute of Technology, Chennai, India.

PA

P Anandhakumar

Dr. Anandhakumar is a professor in the Department of Information Technology at Anna University, Chennai. He has completed his doctorate in the year 2006 from Anna University. He has produced 17 PhD's in the field of Image Processing, Cloud Computing, Multimedia technology and Machine Learning. His ongoing research lies in the field of Digital Twin Technology, Machine Learning and Artificial Intelligence. He has published more than 150 papers indexed in SCI, SCOPUS, WOS etc.

View book on ScienceDirect

Read Applying Computational Intelligence for Social Good on ScienceDirect