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Predicting Individual Trip Destinations with Artificial Potential Fields
6 references·1 citing·28 second hop
Predicting Individual Trip Destinations with Artificial Potential Fields (2017)Predicting Individual Trip Destinations w…Far Out: Predicting Long-Term Human Mobility (2021)Far Out: Predicting Long-Term…Where and what: Using smartphones to predict next locations and applications in daily life (2013)Where and what: Using smartph…NextPlace: A Spatio-temporal Prediction Framework for Pervasive Systems (2011)NextPlace: A Spatio-temporal …Activity-Aware Map: Identifying Human Daily Activity Pattern Using Mobile Phone Data (2010)Activity-Aware Map: Identifyi…Understanding mobility based on GPS data (2008)Understanding mobility based …Using GPS to learn significant locations and predict movement across multiple users (2003)Using GPS to learn significan…A Destination Prediction Model for Individual Passengers in Urban Rail Transit (2020)A Destination Prediction Mode…Reality mining: sensing complex social systems (2005)Understanding individual human mobility patterns (2008)Limits of Predictability in Human Mobility (2010)Development of origin–destination matrices using mobile phone call data (2014)Social Sensing: A New Approach to Understanding Our Socioeconomic Environments (2015)The promises of big data and small data for travel behavior (aka human mobility) analysis (2016)Friendship and mobility (2011)Zooming into individuals to understand the collective: A review of trajectory-based travel behaviour studies (2014)Mobile Big Data: The Fuel for Data-Driven Wireless (2017)A multi-dimension framework for value creation through Big Data (2020)"I'd be overwhelmed, but it's just one more thing to do" (2002)The Museum Wearable: real-time sensor-driven understanding of visitors' interests for personalized visually-augmented museum experiences (2002)Learning significant locations and predicting user movement with GPS (2003)Learning and inferring transportation routines (2007)Learning transportation mode from raw gps data for geographic applications on the web (2008)Urban Computing (2014)A survey of methods for time series change point detection (2016)Human mobility: Models and applications (2018)Estimation of Passenger Route Choice Pattern Using Smart Card Data for Complex Metro Systems (2016)Spatio-Temporal Analysis of Passenger Travel Patterns in Massive Smart Card Data (2017)Individual mobility prediction using transit smart card data (2018)Practical model with strong interpretability and predictability: An explanatory model for individuals' destination prediction considering personal and crowd travel behavior (2020)Building a validation measure for activity-based transportation models based on mobile phone data (2014)Mining smartphone data for app usage prediction and recommendations: A survey (2017)LSTM-Based Deep Learning Model for Predicting Individual Mobility Traces of Short-Term Foreign Tourists (2020)gSCorr (2012)Interdependence and predictability of human mobility and social interactions (2013)Analyzing large-scale human mobility data: a survey of machine learning methods and applications (2018)
this work references cited by second hop

References

  • 2008Understanding mobility based on GPS data1,152 cited
  • 2003Using GPS to learn significant locations and predict movement across multiple users1,063 cited
  • 2010Activity-Aware Map: Identifying Human Daily Activity Pattern Using Mobile Phone Data287 cited
  • 2011NextPlace: A Spatio-temporal Prediction Framework for Pervasive Systems277 cited
  • 2013Where and what: Using smartphones to predict next locations and applications in daily life137 cited
  • 2021Far Out: Predicting Long-Term Human Mobility99 cited

Cited by

  • 2020A Destination Prediction Model for Individual Passengers in Urban Rail Transit6 cited

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