A Prediction Precision Inference Method for Passenger Alighting Station Based on the Condition Hypothesis

[1]  Wenyang Guo,et al.  A geographical location prediction method based on continuous time series Markov model , 2018, PloS one.

[2]  Qing Liu,et al.  A Hybrid Prediction Model for Moving Objects , 2008, 2008 IEEE 24th International Conference on Data Engineering.

[3]  Marta C. González,et al.  Understanding individual human mobility patterns , 2008, Nature.

[4]  Tomohiro Yamamura,et al.  A Driver Behavior Recognition Method Based on a Driver Model Framework , 2000 .

[5]  Thad Starner,et al.  Using GPS to learn significant locations and predict movement across multiple users , 2003, Personal and Ubiquitous Computing.

[6]  Cecilia Mascolo,et al.  Mining User Mobility Features for Next Place Prediction in Location-Based Services , 2012, 2012 IEEE 12th International Conference on Data Mining.

[7]  Nicholas Jing Yuan,et al.  Reconstructing individual mobility from smart card transactions: a collaborative space alignment approach , 2014, Knowledge and Information Systems.

[8]  Cecilia Mascolo,et al.  NextPlace: A Spatio-temporal Prediction Framework for Pervasive Systems , 2011, Pervasive.

[9]  Marc-Olivier Killijian,et al.  Next place prediction using mobility Markov chains , 2012, MPM '12.

[10]  Xing Xie,et al.  Analyzing Location Predictability on Location-Based Social Networks , 2014, PAKDD.

[11]  Daniel Gatica-Perez,et al.  Contextual conditional models for smartphone-based human mobility prediction , 2012, UbiComp.

[12]  Aixin Sun,et al.  A Survey of Location Prediction on Twitter , 2017, IEEE Transactions on Knowledge and Data Engineering.

[13]  Hans-Peter Kriegel,et al.  A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise , 1996, KDD.

[14]  Bin Jiang,et al.  Characterizing the human mobility pattern in a large street network. , 2009, Physical review. E, Statistical, nonlinear, and soft matter physics.

[15]  Ying Long,et al.  Finding Public Transportation Community Structure Based on Large-Scale Smart Card Records in Beijing , 2015 .

[16]  Nan Zou,et al.  Estimating a Transit Passenger Trip Origin-Destination Matrix Using Automatic Fare Collection System , 2011, DASFAA Workshops.

[17]  Zhang Zhi-gang,et al.  Individual station estimation from smart card transactions , 2017 .

[18]  Alex Erath,et al.  Estimating Dynamic Workplace Capacities by Means of Public Transport Smart Card Data and Household Travel Survey in Singapore , 2013 .

[19]  Bruno Martins,et al.  Predicting future locations with hidden Markov models , 2012, UbiComp.

[20]  Ran El-Yaniv,et al.  On Prediction Using Variable Order Markov Models , 2004, J. Artif. Intell. Res..

[21]  Albert-László Barabási,et al.  Understanding individual human mobility patterns , 2008, Nature.

[22]  Daniel Gatica-Perez,et al.  Discovering places of interest in everyday life from smartphone data , 2011, Multimedia Tools and Applications.

[23]  Wen-Jing Hsu,et al.  Predictability of individuals' mobility with high-resolution positioning data , 2012, UbiComp.

[24]  Xing Xie,et al.  Mining user similarity based on location history , 2008, GIS '08.

[25]  Alex Pentland,et al.  Modeling and Prediction of Human Behavior , 1999, Neural Computation.

[26]  Soong Moon Kang,et al.  Structure of Urban Movements: Polycentric Activity and Entangled Hierarchical Flows , 2010, PloS one.

[27]  Michael Batty,et al.  Detecting the dynamics of urban structure through spatial network analysis , 2014, Int. J. Geogr. Inf. Sci..

[28]  Qingquan Li,et al.  Map-matching algorithm for large-scale low-frequency floating car data , 2014, Int. J. Geogr. Inf. Sci..

[29]  Albert-László Barabási,et al.  Limits of Predictability in Human Mobility , 2010, Science.

[30]  T. Geisel,et al.  The scaling laws of human travel , 2006, Nature.