Muutke küpsiste eelistusi

Convergence of Big Data Technologies and Computational Intelligent Techniques [Kõva köide]

Edited by
  • Formaat: Hardback, 233 pages, kõrgus x laius: 279x216 mm, kaal: 363 g
  • Ilmumisaeg: 16-Sep-2022
  • Kirjastus: IGI Global
  • ISBN-10: 1668452642
  • ISBN-13: 9781668452646
Teised raamatud teemal:
  • Formaat: Hardback, 233 pages, kõrgus x laius: 279x216 mm, kaal: 363 g
  • Ilmumisaeg: 16-Sep-2022
  • Kirjastus: IGI Global
  • ISBN-10: 1668452642
  • ISBN-13: 9781668452646
Teised raamatud teemal:
Advanced computational intelligence techniques have been designed and developed in recent years to cope with various big data challenges and provide fast and efficient analytics that assist in making critical decisions. With the rapid evolution and development of internet-based services and applications, this technology is receiving attention from researchers, industries, and academic communities and requires additional study.

Convergence of Big Data Technologies and Computational Intelligent Techniques considers recent advancements in big data and computational intelligence across fields and disciplines and discusses the various opportunities and challenges of adoption. Covering topics such as deep learning, data mining, smart environments, and high-performance computing, this reference work is crucial for computer scientists, engineers, industry professionals, researchers, scholars, practitioners, academicians, instructors, and students.
Preface xiv
Acknowledgment xvii
Introduction xviii
Chapter 1 Advent of Big Data in Urban Transportation for Smart Cities: Current Progress, Trends, and Future Challenges
1(60)
Bhargav Naidu Matcha
Sivakumar Sivanesan
K. C. Ng
Se Yong Eh Noum
Aman Sharma
Chapter 2 Twitter Data Analysis Using Apache Streaming
61(15)
Lavanya Sendhilvel
Kush Diwakar Desai
Simran Adake
Rachit Bisaria
Hemang Ghanshyambhai Vekariya
Chapter 3 Transport Data Analytics With Selection of Tools and Techniques
76(14)
Jayanthi Ganapathy
R. Purushothaman
M. Ramya
C. Joselyn Diana
Chapter 4 Towards Design of Brain Tumor Detection Framework Using Deep Transfer Learning Techniques
90(14)
Prince Rajak
Anjali Sagar Jangde
Govind P. Gupta
Chapter 5 Big Data in the Context of Digital Journalism
104(9)
Mustafa Eren Akpinar
Chapter 6 COVID-19 Vaccination Perceptions, Issues, and Challenges: An Analysis of Tweets Using Machine Learning Models
113(34)
Sreekantha Desai Karanam
M. Krithin
R. V. Kulkarni
Chapter 7 Heart Disease Prediction Framework Using Soft Voting-Based Ensemble Learning Techniques
147(19)
Omprakash Nayak
Tejaswini Pallapothala
Govind P. Gupta
Chapter 8 IoT-Based Health Risk Prediction by Collecting and Analyzing HIIT Data in Real Time Using Edge Computing
166(20)
Shrikrishn Bansal
Rajbir Kaur
Chapter 9 Robust Dimensionality Reduction: A Resistant Search for the Relevant Information in Complex Data
186(25)
Jan Kalina
Compilation of References 211(17)
About the Contributors 228(4)
Index 232
Govind P. Gupta is currently working as Assistant Professor in National Institute of Technology, Raipur. He has done PhD from IIT, Roorkee. His area of interests are Computer Networking, Distributed Algorithms design for Wireless Sensor Networks, Performance Analysis, Big Data Processing, Parallel and Distributed Computing, Design & Analysis of Algorithms.