Objective Information Theory (SpringerBriefs in Computer Science)
Language: English
Published by Springer, 2023
- Softcover
- New
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- Title
- Objective Information Theory (SpringerBriefs in Computer Science)
- Author
- Xu, Jianfeng; Wang, Shuliang; Liu, Zhenyu; Wang, Yashi; Wang, Yingfei; Dang, Yingxu
- Publisher
- Springer
- Publication year
- 2023
- Condition
- New
- Binding
- Soft cover
- Language
- English
- ISBN 10
- 9811999287
- ISBN 13
- 9789811999284
- Series
- Book 30 of 103: SpringerBriefs in Computer Science
Objective Information Theory (OIT) is proposed to represent and compute the information in a large-scale complex information system with big data in this monograph. To formally analyze, design, develop, and evaluate the information, OIT interprets the information from essential nature, measures the information from mathematical properties, and models the information from concept, logic, and physic. As the exemplified applications, Air Traffic Control System (ATCS) and Smart Court SoSs (System of Systems) are introduced for practical OITs.
This Open Access book can be used as a technical reference book in the field of information science and also a reference textbook for senior students and graduate ones in related majors.
"Synopsis" may belong to another edition of this title.
About the Author
Xu Jianfeng received his Ph.D. in software science from Nanjing University in 2001. He is currently the director of Information Technology Service Center of People's Court. His research interests include information systems, systematic engineering of smart court, objective information theory, artificial intelligence, and big data.
Wang Shuliang (corresponding author) is a professor at Beijing Institute of Technology and the executive dean of E-Government Institute. He mainly studies data mining and has written the popular monograph Spatial Data Mining published by Springer Nature. His achievements won him the first prize at the National Science and Technology Progress Award, National Excellent Doctoral Dissertation, and so on.
Liu Zhenyu is an associate professor in the School of Law Information Management at China University of Political Science and Law. He obtained his Ph.D. degree from the University of Birmingham in the UK. His research interests include reinforcement learning, nature-inspired computation, machine learning, and the real-world applications of artificial intelligence in the fields of legal practice.
Wang Yashi is a professor at the School of Law Information Management at China University of Political Science and Law. Her main research areas are applied probability theory, reliability theory, and random risk comparison.
Wang Yingfei received her Ph.D. degree in computational mathematics from Wuhan University in 2016. She is currently with Information Technology Service Center of People's Court. Her current research interests include objective information theory, big data, complex networks, and nonlinear dynamics.
Dang Yingxu is a master student at the School of Computer Science and Technology, Beijing Institute of Technology. His research interests include data mining, artificial intelligence, and object prediction.
"About the title" may belong to another edition of this title.
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