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Applying Computational Intelligence for Social Good

Applying Computational Intelligence for Social Good

Track, Understand and Build a Better world
Buch | Hardcover
503 Seiten
2024
Academic Press Inc (Verlag)
978-0-323-88544-7 (ISBN)
CHF 219,95 inkl. MwSt
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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.

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. 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.

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

Erscheinungsdatum
Reihe/Serie Advances in Computers
Mitarbeit Herausgeber (Serie): Preetha Evangeline David, P Anandhakumar
Verlagsort Oxford
Sprache englisch
Maße 152 x 229 mm
Gewicht 450 g
Themenwelt Mathematik / Informatik Informatik Software Entwicklung
Mathematik / Informatik Mathematik
ISBN-10 0-323-88544-6 / 0323885446
ISBN-13 978-0-323-88544-7 / 9780323885447
Zustand Neuware
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