Description
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.- Provides a unique opportunity to present the work on the state-of-the-art of metaheuristics approach in the area of big data processing developing automated and intelligent models- Explains different, feasible applications and case studies where cognitive computing can be successfully implemented in big data analytics using metaheuristics algorithms- Provides a snapshot of the latest advances in the contribution of metaheuristics frameworks in cognitive big data applications to solve optimization problems
Table of Contents
A. Foundations and Architectural Models of Cognitive Big Data and Meta heuristics1. Cognitive Computing fundamentals like perception, memory, reasoning, emotion, and problem solving2. Cognitive Computing techniques using artificial intelligence, pattern and speech recognition, and natural language processing3. Cognitive approaches within data mining and machine learning techniques4. Big Data Infrastructure for Cognition and Distributed Data Centers for Cognition5. Meta heuristics in classification, clustering and frequent pattern mining problems6. Nature-inspired computing and Optimization algorithms7. Meta heuristics and swarm intelligence approach8. Use of Computational intelligence and Intelligent computing approaches in engineering domains9. Big Data, Clouds and Internet of Things (IoT)10. Dimensionality reduction models with Meta heuristics11. Neuro-evolutionary and fuzzy models in big data and cognitive analytics12. Innovative methods for cognitive business big data analytics13. Cognitive techniques for mining unstructured, spatial-temporal, streaming and multimedia data14. Data-driven large scale optimization architectures15. Ensemble learning with Meta heuristics optimizationB. Application Domains and use of Cognitive Big data with Meta heuristics16. Applications in Logistics, Transportation and Supply Chain Management17. Cognitive Sensor-Networks applications18. Algorithm development for big data analysis in E-health and Telemedicine19. Biomedical Image Processing and Big Data Applications20. Data Applications of Cognitive Communication21. Intelligent distributed applications in e-commerce22. Applications in Economics and Finance23. Applications in Aeronautics24. Applications in financial analysis25. Applications in Cyber security and Intelligence26. Applications in Traffic Optimization27. Applications in routing of energy efficient communication networks28. Other Miscellaneous applications
