Methodologies and Applications of Computational Statistics for Machine Intelligence

Methodologies and Applications of Computational Statistics for Machine Intelligence

Indexed In: SCOPUS
Release Date: June, 2021|Copyright: © 2021 |Pages: 277
DOI: 10.4018/978-1-7998-7701-1
ISBN13: 9781799877011|ISBN10: 1799877019|EISBN13: 9781799877035
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Description & Coverage
Description:

With the field of computational statistics growing rapidly, there is a need for capturing the advances and assessing their impact. Advances in simulation and graphical analysis also add to the pace of the statistical analytics field. Computational statistics play a key role in financial applications, particularly risk management and derivative pricing, biological applications including bioinformatics and computational biology, and computer network security applications that touch the lives of people. With high impacting areas such as these, it becomes important to dig deeper into the subject and explore the key areas and their progress in the recent past.

Methodologies and Applications of Computational Statistics for Machine Intelligence serves as a guide to the applications of new advances in computational statistics. This text holds an accumulation of the thoughts of multiple experts together, keeping the focus on core computational statistics that apply to all domains. Covering topics including artificial intelligence, deep learning, and trend analysis, this book is an ideal resource for statisticians, computer scientists, mathematicians, lecturers, tutors, researchers, academic and corporate libraries, practitioners, professionals, students, and academicians.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

  • Artificial Intelligence
  • Bi-Static Radar
  • Computational Statistics
  • Data Mining
  • Deep Learning
  • Machine Intelligence
  • Microblog Data
  • Robotics
  • Software Engineering
  • Steganography
  • Trend Analysis
  • Unsupervised Summarization Approach
  • Vector Machines
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Editor/Author Biographies

Debabrata Samanta is presently working as Assistant Professor, Department of Computer Science, CHRIST (Deemed to be University), Bangalore, India. He obtained his B.Sc. (Physics Honors), from Calcutta University; Kolkata, India. He obtained his MCA, from the Academy of Technology, under WBUT, West Bengal. He obtained his PhD in Computer Science and Eng. from National Institute of Technology, Durgapur, India, in the area of SAR Image Processing. His areas of interest are SAR Image Analysis, Video surveillance, Heuristic algorithm for image classification, Deep Learning Framework for Detection and Classification, Blockchain, Statistical Modelling, Wireless Adhoc Network, Natural Language Processing,V2I Communication. He is the owner of 17 Indian Patents. He has authored and coauthored over 134 research papers in international journal (SCI/SCIE/ESCI/Scopus) and conferences including IEEE, Springer and Elsevier Conference proceedings. He has received “Scholastic Award” at 2nd International conference on Computer Science and IT application, CSIT-2011, Delhi, India. He has published 9 books, available for sale on Amazon and Flipkart.

Raghavendra Rao Althar has obtained his Bachelor's in Mechanical Engineering from VTU and MBA in Operations Management from Indira Gandhi Open University. His area of interest is in application of Data Science in Software Development Processes. He is Currently researching as Quality Management Specialist in a Software Development team of Insurance domain-based company. For last 15 years, he has been researching on building Quality Management Systems for various domains like manufacturing, Retail, Telecom and Software industries, based on International Standards like ISO, Six sigma and best Global practices for industry. Adopting best practices of Data Science to optimize Software Development processes and connected Business Processes has been the recent focus area. He is Six sigma Black Belt certified and Quality Management & Information Security Audit Standards certified practitioner. He is pursuing Doctor of Philosophy in Data Science from Christ (Deemed to be University), Bangalore, India since June 2020. ORCIDID: 0000-0001-5859-0662.

Sabyasachi Pramanik is a professional IEEE member. He obtained a PhD in Computer Science and Engineering from Sri Satya Sai University of Technology and Medical Sciences, Bhopal, India. Presently, he is an Associate Professor, Department of Computer Science and Engineering, Haldia Institute of Technology, India. He has many publications in various reputed international conferences, journals, and book chapters (Indexed by SCIE, Scopus, ESCI, etc). He is doing research in the fields of Artificial Intelligence, Data Privacy, Cybersecurity, Network Security, and Machine Learning. He also serves on the editorial boards of several international journals. He is a reviewer of journal articles from IEEE, Springer, Elsevier, Inderscience, IET and IGI Global. He has reviewed many conference papers, has been a keynote speaker, session chair, and technical program committee member at many international conferences. He has authored a book on Wireless Sensor Network. He has edited 8 books from IGI Global, CRC Press, Springer and Wiley Publications.
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