Cognitive Big Data Intelligence with a Metaheuristic Approach presents an exact and compact organization of content relating to the latest metaheuristics methodologies based on new challenging big data application domains and cognitive computing. The combined model of cognitive big data intelligence with metaheuristics methods can be used to analyze emerging patterns, spot business opportunities, and take care of critical process-centric issues in real-time. Various real-time case studies and implemented works are discussed in this book for better understanding and additional clarity. This…mehr
Cognitive Big Data Intelligence with a Metaheuristic Approach presents an exact and compact organization of content relating to the latest metaheuristics methodologies based on new challenging big data application domains and cognitive computing. The combined model of cognitive big data intelligence with metaheuristics methods can be used to analyze emerging patterns, spot business opportunities, and take care of critical process-centric issues in real-time. Various real-time case studies and implemented works are discussed in this book for better understanding and additional clarity.
This book presents an essential platform for the use of cognitive technology in the field of Data Science. It covers metaheuristic methodologies that can be successful in a wide variety of problem settings in big data frameworks.
Dr. Sushruta Mishra is working as an Assistant Professor in the School of Computer Engineering, KIIT University, Bhubaneswar, Odisha, India. He pursued his M.Tech from IIIT, Bhubaneswar in 2012 and has completed his Ph.D in Computer Science from KIIT University, Bhubaneswar, Odisha, India in 2017. Dr. Mishra has more than 7 years of teaching experience in various educational institutions. He has handled many subjects such as Computer networks, Data mining, Software engineering, Machine learning etc during his academic experience. His research interest includes Image processing, Machine Learning, Internet of Things and Cognitive computing. He has published several research articles in reputed scopus indexed International Journals, Edited books and Conferences.
Inhaltsangabe
A. Foundations and Architectural Models of Cognitive Big Data and Meta heuristics 1. Cognitive Computing fundamentals like perception, memory, reasoning, emotion, and problem solving 2. Cognitive Computing techniques using artificial intelligence, pattern and speech recognition, and natural language processing 3. Cognitive approaches within data mining and machine learning techniques 4. Big Data Infrastructure for Cognition and Distributed Data Centers for Cognition 5. Meta heuristics in classification, clustering and frequent pattern mining problems 6. Nature-inspired computing and Optimization algorithms 7. Meta heuristics and swarm intelligence approach 8. Use of Computational intelligence and Intelligent computing approaches in engineering domains 9. Big Data, Clouds and Internet of Things (IoT) 10. Dimensionality reduction models with Meta heuristics 11. Neuro-evolutionary and fuzzy models in big data and cognitive analytics 12. Innovative methods for cognitive business big data analytics 13. Cognitive techniques for mining unstructured, spatial-temporal, streaming and multimedia data 14. Data-driven large scale optimization architectures 15. Ensemble learning with Meta heuristics optimization
B. Application Domains and use of Cognitive Big data with Meta heuristics 16. Applications in Logistics, Transportation and Supply Chain Management 17. Cognitive Sensor-Networks applications 18. Algorithm development for big data analysis in E-health and Telemedicine 19. Biomedical Image Processing and Big Data Applications 20. Data Applications of Cognitive Communication 21. Intelligent distributed applications in e-commerce 22. Applications in Economics and Finance 23. Applications in Aeronautics 24. Applications in financial analysis 25. Applications in Cyber security and Intelligence 26. Applications in Traffic Optimization 27. Applications in routing of energy efficient communication networks 28. Other Miscellaneous applications
A. Foundations and Architectural Models of Cognitive Big Data and Meta heuristics 1. Cognitive Computing fundamentals like perception, memory, reasoning, emotion, and problem solving 2. Cognitive Computing techniques using artificial intelligence, pattern and speech recognition, and natural language processing 3. Cognitive approaches within data mining and machine learning techniques 4. Big Data Infrastructure for Cognition and Distributed Data Centers for Cognition 5. Meta heuristics in classification, clustering and frequent pattern mining problems 6. Nature-inspired computing and Optimization algorithms 7. Meta heuristics and swarm intelligence approach 8. Use of Computational intelligence and Intelligent computing approaches in engineering domains 9. Big Data, Clouds and Internet of Things (IoT) 10. Dimensionality reduction models with Meta heuristics 11. Neuro-evolutionary and fuzzy models in big data and cognitive analytics 12. Innovative methods for cognitive business big data analytics 13. Cognitive techniques for mining unstructured, spatial-temporal, streaming and multimedia data 14. Data-driven large scale optimization architectures 15. Ensemble learning with Meta heuristics optimization
B. Application Domains and use of Cognitive Big data with Meta heuristics 16. Applications in Logistics, Transportation and Supply Chain Management 17. Cognitive Sensor-Networks applications 18. Algorithm development for big data analysis in E-health and Telemedicine 19. Biomedical Image Processing and Big Data Applications 20. Data Applications of Cognitive Communication 21. Intelligent distributed applications in e-commerce 22. Applications in Economics and Finance 23. Applications in Aeronautics 24. Applications in financial analysis 25. Applications in Cyber security and Intelligence 26. Applications in Traffic Optimization 27. Applications in routing of energy efficient communication networks 28. Other Miscellaneous applications
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