Intelligent Processing Algorithms and Applications for GPS Positioning Data of Qinghai-Tibet Railway, 1st ed. 2019
Case Study on Qinghai-Tibet Railway

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Language: English
Cover of the book Intelligent Processing Algorithms and Applications for GPS Positioning Data of Qinghai-Tibet Railway

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157 p. · 15.5x23.5 cm · Hardback
Taking the Qinghai?Tibet Railway as an example, this book introduces intelligent processing for Global Positioning Data (GPS) data. Combining theory with practical applications, it provides essential insights into the Chinese Qinghai?Tibet Railway and novel methods of data processing for GPS satellite positioning, making it a valuable resource for all those working with train control systems, train positioning systems, satellite positioning, and intelligent data processing. As satellite positioning guarantees the safe and efficient operation of train control systems, it focuses on how to best process the GPS data collected, including methods for error detection, reduction and information fusion.
Satellite navigation system applying in railway.- Qinghai-Tibet Railway: history, technical difficulties and future.- Incremental Train Control System for Qinghai-Tibet Railway.- Key Technical Issues for GPS Positioning System.- Integrated error-detecting method for GPS data points by measurement knowledge.- Data reduction models and algorithms for GPS data points.- Information fusion algorithms for multiple GPS data.- Object-oriented digital GPS map for train control system based on graph theory.- Summary and Outlook.

Mr. Dewang Chen is a professor of Fuzhou University. He published lots of high-quality articles and won many awards, such as the Second Prize for Science and Technology Progress of the Ministry of Railway of China in 2007, the Young Scientific Star of Beijing in 2010, and the Young Scientist Prize of ZhanTianyou Fund in 2015 for his research and the field test in Qinghai-Tibet railway.Dewang Chen, received the Ph.D degree in control theory from Chinese Academy of Sciences, Beijing, China, in 2003. In 2009, he was a Visiting Scholar with the Department of Electrical Engineering and Computer Science, University of California, Berkeley, CA, USA. From 2011 to 2014, he was a full Professor with State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing. In 2012, he was a Visiting Researcher with the Center for Industrial and Applied Mathematics, University of South Australia, Adelaide, Australia. He is currently a Minjiang Distinguished Professor with the College of Mathematics and Computer Science, and the Founding Dean of the Key Laboratory of Intelligent Metro of Universities of Fujian Province, Fuzhou University, Fuzhou, China. He is the author of more than 100 papers, three monographs and four patents. His current research interests include artificial intelligence, big data, machine learning, soft computing, and intelligent transportation systems. Dr. Chen has served on program committees of more than 15 international conferences. He has been serving as an IEEE senior member and  Associate Editor for ''IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS'' since 2014. 

Ruijun Cheng received the M.S. degree and Ph.D. degree from the State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, China, in 2014 and 2019. In 2018, he was a Visiting Scholar with the Department of Electrical Engineering and Computer Engineering, University of Massachusetts (UMass), Dartmouth, MA

Introduces Global Positioning Data (GPS) satellite positioning in the context of the Qinghai–Tibet Railway in an easily understandable way Processes and analyzes a large volume of GPS data on the Qinghai–Tibet Railway Offers novel methods of error detection, reduction, and information fusion for GPS data