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Full Description
Intelligent systems are technologically advanced machines that perceive and respond to the world around them. Artificial Intelligence and Machine Learning for Smart Community: Concepts and Applications presents the evolution, challenges, and limitations of the application of machine learning and artificial intelligence to intelligent systems and smart communities.
Covers the core and fundamental aspects of artificial intelligence, machine learning, and computational algorithms in smart intelligent systems
Discusses the integration of artificial intelligence with machine learning using mathematical modeling
Elaborates concepts like supervised and unsupervised learning, and machine learning algorithms, such as linear regression, logistic regression, random forest, and performance evaluation matrices
Introduces modern algorithms such as convolutional neural networks and support vector machines
Presents case studies on smart healthcare, smart traffic management, smart buildings, autonomous vehicles, smart education, modern community, and smart machines
Artificial Intelligence and Machine Learning for Smart Community: Concepts and Applications is primarily written for graduate students and academic researchers working in the fields of computer science and engineering, electrical engineering, and information technology. Seasonal Blurb: This reference text presents the most recent and advanced research on the application of artificial intelligence and machine learning on intelligent systems. It will discuss important topics such as business intelligence, reinforcement learning, supervised learning, and unsupervised learning in a comprehensive manner.
Contents
Chapter 1. A Detailed Study on deep learning versus machine learning approaches for Pest Classification in Field Crops. Chapter 2. Integration of Artificial Intelligence (AI) and Other Edge Cutting Technologies. Chapter 3. A detailed case study on various challenges in Vehicular Networks for Smart Traffic Control System using Machine Learning Algorithms. Chapter 4. Revolutionizing Transportation: The Power of Artificial Intelligence. Chapter 5. Smart Education using Explainable Artificial Intelligence (XAI). Chapter 6. Smart Stock Prediction Techniques Using AI-ML. Chapter 7. Smart Community: Concepts & Applications. Chapter 8. Disseminating dynamic traffic information for sustainable mobility and transport.
