Data Statistics of Station Transfer Volume Based on Spark Computing Engine.- Deep Learning Short-Time Interval Passenger Flow Prediction Based on Isomap Algorithm.- Prediction of Subway Interchange Passenger Flow Based on Recurrent Neural Network Time Characteristic Model.- Rail Transit Travel Planning Based on K Nearest Neighbor Path Retrieval Algorithm.- Research on Dynamic Passenger Flow Distribution of Rail Transit Based on Multi-dimensional Euclidean Distance.- Research on Interval Passenger Flow Statistics Based on AFC Data.- Research on Regional Rail Transit Based on Logit Model.- Study on Valid Travel Route Selection of Integrated Passenger Transportation.- Loading and Reinforcing Safety Evaluation of Railway Out-of-Gauge Freight Considering the Dynamic Transportation Process.- Design of Rail Freight Products in the Arduous Mountainous Area on the Plateau under the Concept of Modern Logistics.
About the Author: Tsu-Yang Wu received the Ph.D. degree in the Department of Mathematics, National Changhua University of Education, Taiwan (R.O.C.). Currently, he is Associate Professor at the College of Computer Science and Engineering, Shandong University of Science and Technology, China. In the past, he was Assistant Professor at Harbin Institute of Technology, Shenzhen Campus, and Associate Professor at Fujian University of Technology, China. He serves Executive Editor in the Journal of Network Intelligence (JNI) and Associate Editor in Data Science and Pattern Recognition (DSPR). His research interests include cryptography and network security.
Shaoquan Ni (born 1967, Hubei, China), is a male, Professor, and Director of Southwest Jiaotong University Train Diagram R & D training Center and Transportation Information and Technology Institute. He has presided over 60 research projects, published 3 monographs and more than 160 academic papers, and won 17 awards.
Shu-Chuan Chu received the Ph.D. degree in 2004 from the School of Computer Science, Engineering and Mathematics, Flinders University of South Australia. She joined Flinders in December 2009 after 9 years at the Cheng Shiu University, Taiwan. She has been Research Fellow in the College of Science and Engineering of Flinders University, Australia, from 2009. Currently, she is Research Fellow and Ph.D. Supervisor in the College of Computer Science and Engineering of Shandong University of Science and Technology. Her research interests are mainly in evolutionary computation, swarm intelligence, and wireless sensor networks.
Chi-Hua Chen (Senior Member, IEEE) received his Ph.D. degree in information management from National Chiao Tung University in 2013. He was Research Fellow at Chunghwa Telecom from 2014 to 2018. He has been Full Professor with the College of Mathematics and Computer Science at Fuzhou University from 2018. He has also serves as Chair Professor with the Navigation College at Dalian Maritime University and Consultant with IF-Tek Inc. from 2019. He has published over 300 journal articles, conference articles, and patents. His contributions were published in IEEE Internet of Things Journal, IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, IEICE Transactions on Information and Systems, Journal of Enterprise Information Management, Physica A: Statistical Mechanics and its Applications, Transactions on Emerging Telecommunications Technologies, Wireless Communications and Mobile Computing, WWW'20, SIGIR 2020, and so on. Some of his publications have been recognized as highly cited papers on Web of Science using data from Essential Science Indicators. He serves as Editor for several international journals (e.g., IEEE Access, IEICE Transactions on Information and Systems, Scientific Reports (i.e., one of Nature Research Journals), PLOS ONE, Journal of Database Management, Journal of Applied Statistics, International Journal of Ad Hoc and Ubiquitous Computing, Journal of Organizational and End User Computing, Journal of Medical Imaging and Health Informatics, Intelligent Automation & Soft Computing, Wireless Communications and Mobile Computing, Mobile Information Systems, EURASIP Journal on Wireless Communications and Networking, International Journal of Distributed Sensor Networks, ISPRS International Journal of Geo-Information, Discrete Dynamics in Nature and Society, Mathematical Problems in Engineering, and so on). He also serves as Chair for several international conferences (e.g., WWW'21 Workshop (i.e., a top conference in computer sciences), IEEE APNOMS 2020, IEEE ICC 2020, IEEE BIBM 2020 Workshop, IEEE TrustCom 2020 Workshop, IEEE BigData 2020 Workshop, IEEE ICCE-TW 2020, IEEE IS3C 2020, DASFAA Workshop 2021, IEEE ICCCBDA 2021, IEEE BCD 2021, and so on). His research interests include the Internet of things and machine learning.
Dr. Margarita N. Favorskaya is Professor and Head of Department of Informatics and Computer Techniques at Reshetnev Siberian State University of Science and Technology, Russian Federation. Professor Favorskaya is Member of KES organization since 2010, the IPC Member, and Chair of invited sessions of over 30 international conferences. She serves as Reviewer in international journals (Neurocomputing, Knowledge Engineering and Soft Data Paradigms, Pattern Recognition Letters, and Engineering Applications of Artificial Intelligence), Associate Editor of Intelligent Decision Technologies Journal, International Journal of Knowledge-Based and Intelligent Engineering Systems, International Journal of Reasoning-based Intelligent Systems, Honorary Editor of the International Journal of Knowledge Engineering and Soft Data Paradigms, Reviewer, Guest Editor, and Book Editor (Springer). She is Author/Co-Author of 200 publications and 20 educational manuals in computer science/engineering. She co-authored/co-edited seven books for Springer recently. She supervised nine Ph.D. candidates and presently supervising four Ph.D. students. Her main research interests are smart systems design, digital image and videos processing, remote sensing, pattern recognition, fractal image processing, artificial intelligence, and information technologies.