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.
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.
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
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. Dr. Hrudaya Kumar Tripathy is presently working as
Associate Professor in School of Computer Engineering at KIIT
University, Bhubaneswar, Odisha, India and Program Head of
M.Tech(CSE) courses. He has received M.Tech degree in CSE from IIT
Guwahati in 2006, and obtained Ph.D degree in Computer Science from
Berhampur University, Berhampur, Odisha, India in Computer Science
in 2010. Dr. Tripathy had been a visiting faculty in Asia Pacific
University, Kuala Lumpur, Malaysia and University Utara Malaysia,
Sintok, Malaysia. He is having 20 years of teaching experience with
Post Doctorate from Malaysia. He has handled various subjects like
Software engineering, Machine learning, Business intelligence etc.
His research interest includes Neural Networks, Pattern
Recognition, Software Engineering, Machine learning and Big Data.
He has published several research papers in various journals and
conferences. Besides, academic experience he had been actively
involved in various administrative responsibilities in his previous
job positions. Dr. Tripathy is a senior member of IEEE, life member
of CSI & having membership in other different professional bodies
such as IET, IACSIT, IAENG.Dr. Hrudaya Kumar Tripathy is presently
working as Associate Professor in School of Computer Engineering at
KIIT University, Bhubaneswar, Odisha, India and Program Head of
M.Tech(CSE) courses. He has received M.Tech degree in CSE from IIT
Guwahati in 2006, and obtained Ph.D degree in Computer Science from
Berhampur University, Berhampur, Odisha, India in Computer Science
in 2010. Dr. Tripathy had been a visiting faculty in Asia Pacific
University, Kuala Lumpur, Malaysia and University Utara Malaysia,
Sintok, Malaysia. He is having 20 years of teaching experience with
Post Doctorate from Malaysia. He has handled various subjects like
Software engineering, Machine learning, Business intelligence etc.
His research interest includes Neural Networks, Pattern
Recognition, Software Engineering, Machine learning and Big Data.
He has published several research papers in various journals and
conferences. Besides, academic experience he had been actively
involved in various administrative responsibilities in his previous
job positions. Dr. Tripathy is a senior member of IEEE, life member
of CSI & having membership in other different professional bodies
such as IET, IACSIT, IAENG. Dr. Pradeep Kumar Mallick is currently
working as Senior Associate Professor in the School of Computer
Engineering , Kalinga Institute of Industrial technology (KIIT)
Deemed to be University, Odisha, India .He has also served as
Professor and Head Department of Computer Science and Engineering ,
Vignana Bharathi Institute of Technology, Hyderabad . He has
completed his Post Doctoral Fellow (PDF) in Kongju National
University South Korea , PhD from Siksha Ó’ Anusandhan University,
M. Tech. (CSE) from Biju Patnaik University of Technology (BPUT),
and MCA from Fakir Mohan University Balasore, India. Besides
academics, he is also involved various administrative activities,
Member of Board of Studies, Member of Doctoral Research Evaluation
Committee, Admission Committee etc. His area of research includes
Algorithm Design and Analysis, and Data Mining, Image Processing,
Soft Computing, and Machine Learning. Now he is the editorial
member of Korean Convergence Society for SMB .He has published 9
books and more than 70 research papers in National and
international journals and conference proceedings in his credit
Prof. Arun Kumar Sangaiah received his PhD from the School of
Computer Science and Engineering, VIT University, Vellore, India.
He is currently a Full Professor with National Yunlin University of
Science and Technology, Taiwan. He is also a Professor at the
School of Computing Science and Engineering, VIT University,
Vellore, India. His areas of research interest include machine
learning, Internet of Things, Sustainable Computing. He has
published more than 300 research articles in refereed journals, 11
edited books, one patent (held and filed), as well as four projects
funded by MOST-TAIWAN, one funded by Ministry of IT of India, and
several international projects (CAS, Guangdong Research fund,
Australian Research Council). Dr. Sangaiah has received many
awards, Yushan Young Scholar, Clarivate Top 1% Highly Cited
Researcher (2021,2022, 2023), Top 2% Scientist (Standord
Report-2020,2021,2022, 2023), PIFI-CAS fellowship, Top-10
outstanding researcher, CSI significant Contributor etc. He is also
serving as Editor-in-Chief and/or Associate Editor of various
reputed ISI journals. Dr. Sangaiah is a visiting scientist
(2018-2019) with Chinese Academy of Sciences (CAS), China and
visiting researcher of Université Paris-Est (UPEC), France
(2019-2020) and etc.
Professor Gyoo-Soo Chae works in the Division of ICT at Baekseok
University, Cheonan in South Korea.
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