Applying Computational Intelligence for Social Good

Track, Understand and Build a Better world

AvPreetha Evangeline David,P. Anandhakumar

Inbunden, Engelska, 2024

Del 132 i serien Advances in Computers

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Beskrivning

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.

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

Produktinformation

Utgivningsdatum:2024-01-17
Mått:152 x 229 x undefined mm
Vikt:450 g
Format:Inbunden
Språk:Engelska
Serie:Advances in Computers
Antal sidor:503
Förlag:Elsevier Science
ISBN:9780323885447

Utforska kategorier

Matematik inom Naturvetenskap och teknik
Programmeringsböcker inom Data och IT

Mer om författaren

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.

Innehållsförteckning

1. Why is implementing Computational Intelligence for social good so challenging? Principles and its ApplicationPreetha Evangeline and Anandhakumar P2. Smart crisis management system for road accidents using Geo-Spacial Machine Learning TechniquesCephas Paul Edward3. Residential Energy Management System (REMS) Using Machine LearningG Ramya and R Ramaprabha4. Text-Based Personality Prediction using XLNetAshok Kumar Jayaraman and Gayathri Ananthakrishnan5. Articulating the power of reasoning and gathering data for Information security and JusticePreetha Evangeline and Anandhakumar P6. Blockchain Smart Contracts Quality Measurement using Bayesian NetworksLakshminarayana Kodavali I and K. Sathiyamurthy7. Short-Term Wind Power Prediction Using Deep Learning ApproachesAnandhakumar P and Alex Luke K.A8. Cyber Data Trend and Intelligent ComputingAtma Sahu and Preetha Evangeline9. Demystifying the Edge IntelligencePethuru Raj Chelliah Sr. and Preetha Evangeline10. An Automatic Path Navigation for Visually Challenged People using Deep Q LearningMuthurajkumar S11. Delineating Computational Intelligence during Epidemic Emergencies and OutbreaksPreetha Evangeline and V. Vivek12. Deep Learning Model for Computation, Calibration and Estimation of Biotic Stress in CropsPreetha Evangeline and Anandhakumar P13. Weather Nowcasting Model: A Rough Set ApproachS. Anbarasu and Anandhakumar P14. Intelligent methodologies for Assessment of Plant exracts as protectants against storage pestsGowthamy U. and Hemalatha G.15. Automatic programming (source code generator) based on an ontological modelPreetha Evangeline and Rex Vinod. A