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Using geographically weighted regression to forecast rail demand in the Sydney Region
5 references·4 citing·41 second hop
Using geographically weighted regression to forecast rail demand in the Sydney Region (2013)Using geographically weighted regression …Trip end models of local rail demand in England and Wales (2008)Trip end models of local rail…Sketch Models to Forecast Commuter and Light Rail Ridership: Update toTCRP Report 16 (2006)Sketch Models to Forecast Com…Geographically Weighted Regression: The Analysis of Spatially Varying Relationships (2002)Geographically Weighted Regre…The Future of Spatial Analysis in the Social Sciences (1999)The Future of Spatial Analysi…Demand Forecasting for New Local Rail Stations and Services (1991)Demand Forecasting for New Lo…Spatio-Temporal Investigation of Public Transport Demand Using Smart Card Data (2023)Spatio-Temporal Investigation…Local modeling as a solution to the lack of stop-level ridership data (2023)Local modeling as a solution …A review of demand forecasting models and methodological developments within tourism and passenger transportation industry (2019)A review of demand forecastin…Road Network Accessibility and Socio-economic Disadvantage Across Adelaide Metropolitan Area (2016)Road Network Accessibility an…Urban rail in America: An exploration of criteria for fixed-guideway transit (1982)Attitudinal Market Segmentation Approach to Mode Choice and Ridership Forecasting: Structural Equation Modeling (2003)A GIS-based appraisal framework for new local railway stations and services (2012)Factors that Influence Urban Streetcar Ridership in the United States (2013)Study design impacts on built environment and transit use research (2019)Spatial Econometrics: Methods and Models (1988)Increasing Returns and Economic Geography (1990)Local Indicators of Spatial Association—LISA (1995)Democratic Dominoes Revisited (2003)Economic Structure and Regional Disparity in China: Beyond the Kuznets Transition (2010)Policies for carbon-zero targets: Examining the spillover effects of renewable energy and patent applications on environmental quality in Europe (2023)Geographically Weighted Regression (1998)The demand for public transport: a practical guide (2004)Estimating local car ownership models (2006)Evaluating efficiency of passenger railway stations: A DEA approach (2016)Does residential property price benefit from light rail in Sydney? (2018)Multiscale spatial analysis of metro usage and its determinants for sustainable urban development in Shenzhen, China (2022)Comparing alternative approaches to measuring the geographical accessibility of urban health services: Distance types and aggregation-error issues (2008)Big geo-data unveils influencing factors on customer flow dynamics within urban commercial districts (2024)Four-step framework for untangling place and mobility components of access: An equal opportunity perspective (2024)Transit access effectiveness in American metropolitan areas (2024)Fuzzy sets (1965)Time Series Analysis: Forecasting and Control. (1978)Fuzzy sets (1996)The role of disaggregated search data in improving tourism forecasts: Evidence from Sri Lanka (2020)Demand forecasting model using hotel clustering findings for hospitality industry (2021)Systematic review of passenger demand forecasting in aviation industry (2023)A Computer Movie Simulating Urban Growth in the Detroit Region (1970)Geographically Weighted Regression: A Method for Exploring Spatial Nonstationarity (1996)Geographically Weighted Regression: The Analysis of Spatially Varying Relationships (2004)Spatial Modeling of Travel Demand Accounting for Multicollinearity and Different Sampling Strategies: A Stop‐Level Case Study (2024)Transport challenges in Brazil and research opportunities (2024)Application of Spatial Data and Analysis for Bus Transportation Optimization and Planning: A State-of-the-Art Review (2026)Transportation Research Part A: Policy and Practice (2009)Salvador Urban Network Transportation (SUNT): A Landmark Spatiotemporal Dataset for Public Transportation (2025)Investigating the spatiotemporal variability of mobility-based centrality in Seoul using mobile phone signaling data (2026)Methods to account for spatial autocorrelation in the analysis of species distributional data: a review (2007)A measure of spatial stratified heterogeneity (2016)Cross‐validation strategies for data with temporal, spatial, hierarchical, or phylogenetic structure (2016)Estimating the Benefits of Traffic Calming on Through Routes: A Choice Experiment Approach (2002)Modelling local rail demand in South Wales (2009)
this work references cited by second hop

References

  • 2002Geographically Weighted Regression: The Analysis of Spatially Varying Relationships3,946 cited
  • 1999The Future of Spatial Analysis in the Social Sciences163 cited
  • 2008Trip end models of local rail demand in England and Wales70 cited
  • 2006Sketch Models to Forecast Commuter and Light Rail Ridership: Update toTCRP Report 1633 cited
  • 1991Demand Forecasting for New Local Rail Stations and Services30 cited

Cited by

  • 2019A review of demand forecasting models and methodological developments within tourism and passenger transportation industry74 cited
  • 2023Spatio-Temporal Investigation of Public Transport Demand Using Smart Card Data16 cited
  • 2016Road Network Accessibility and Socio-economic Disadvantage Across Adelaide Metropolitan Area11 cited
  • 2023Local modeling as a solution to the lack of stop-level ridership data10 cited

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