Applying Computational Intelligence for Social Good (eBook)

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

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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. - 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