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Advances in Computational Collective Intelligence

About the Series

Advances in Computational Collective Intelligence (ACCI) is a new book series from CRC Press and Taylor & Francis. It covers research and developments in the area of collaborative decisions, collective decision making and problem solving, social network analysis, crowdsourcing, animal collective behavior. The ACCI Book Series will publish research on all fields of information technology including the growth and testing of new computational methods, the management and analysis of different types of data, and the implementation of novel engineering applications in all areas of information technology and engineering. It will also publish on inventive treatment methodologies, diagnosis tools and techniques, and finest practices for managers, practitioners and consultants in a wide range of organizations and fields including police, defense, procurement, communications, transport, management, electrical, electronic, and aerospace. The ACCI Book Series:

  • Explores and discusses various aspects of design and development of intelligent technologies in real time environment. It also provides the implementation, integration, and deployment of intelligent technologies and their applications in different emerging fields.
  • Provides important information on the computational collective intelligence methods that have been widely used for solving real world problems, including problem definition, data collection, data preprocessing, modeling, and validation. It also discusses high performance computing offer a wide range of applications and solutions in solving computational problems for any modern organization.
  • Examines the important applications, tools, and methodologies being implemented in the field for the design and development of computer, electrical and engineering systems. It also discusses mathematical tools for solving the complicated problems of engineering systems.
  • Presents varied and timely research in the development, deployment, and management of business information systems and business analytics for sustained organizational development and better business value.
  • About the Series Editor

    Subhendu Kumar Pani received his Ph.D. from Utkal University Odisha, India in the year 2013. He is working as Principal at Krupajal Computer Academy (KCA) Bhubaneswar. He has more than 17 years of teaching and research Experience His research interests include Data mining, Big Data Analysis, web data analytics, Fuzzy Decision Making and Computational Intelligence. He is the recipient of 5 researcher awards. In addition to research, he has guided two PhD students and 31 M. Tech students. He has published 71 International Journal papers (30 Scopus indexed). His professional activities include roles as Associate Editor, Editorial board member and/or reviewer of various International Journals. He is also the book series editor of CRC Press .He is the recipient of 5 research awards. He is Associate with no. of conference societies. He has more than 150 international publications, 5 authored books, 30 edited and upcoming books; 30 book chapters into his account. He is a fellow in SSARSC and life member in IE, ISTE, ISCA,OBA.OMS, SMIACSIT, SMUACEE, CSI. He also regularly serves as a program committee member for numerous national and international conferences.

    Contact Dr. Pani at:  [email protected] or [email protected]

1 Series Title

Per Page

Applications of Machine Learning and Deep Learning on Biological Data

Applications of Machine Learning and Deep Learning on Biological Data

1st Edition


Edited By Faheem Masoodi, Mohammad Quasim, Syed Bukhari, Sarvottam Dixit, Shadab Alam
February 15, 2023

The automated learning of machines characterizes machine learning (ML). It focuses on making data-driven predictions using programmed algorithms. ML has several applications, including bioinformatics, which is a discipline of study and practice that deals with applying computational derivations to ...

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