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-ime 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
(index)
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
