SZodixStudyAcademic Library
ShelvesOpen access
Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated
Geographically convolutional neural network weighted regression: a method for modeling spatially non-stationary relationships based on a global spatial proximity grid
11 references·0 citing·42 second hopsampled
Geographically convolutional neural network weighted regression: a method for modeling spatially non-stationary relationships based on a global spatial proximity grid (2022)Geographically convolutional neural netwo…A geographically weighted artificial neural network (2021)A geographically weighted art…Social media semantic perceptions on Madrid Metro system: Using Twitter data to link complaints to space (2020)Social media semantic percept…Measuring Bandwidth Uncertainty in Multiscale Geographically Weighted Regression Using Akaike Weights (2020)Measuring Bandwidth Uncertain…Geographically neural network weighted regression for the accurate estimation of spatial non-stationarity (2020)Geographically neural network…Exploring spatial variation of bike sharing trip production and attraction: A study based on Chicago’s Divvy system (2020)Exploring spatial variation o…mgwr: A Python Implementation of Multiscale Geographically Weighted Regression for Investigating Process Spatial Heterogeneity and Scale (2019)mgwr: A Python Implementation…Inference in Multiscale Geographically Weighted Regression (2019)Inference in Multiscale Geogr…Multiscale Geographically Weighted Regression (MGWR) (2017)Multiscale Geographically Wei…Researching Volunteered Geographic Information: Spatial Data, Geographic Research, and New Social Practice (2011)Researching Volunteered Geogr…The Use of Geographically Weighted Regression for Spatial Prediction: An Evaluation of Models Using Simulated Data Sets (2010)The Use of Geographically Wei…Geographically Weighted Regression: A Method for Exploring Spatial Nonstationarity (1996)Geographically Weighted Regre…The wisdom of crowds: why the many are smarter than the few and how collective wisdom shapes business, economies, societies and nations (2004)Citizens as sensors: the world of volunteered geography (2007)4 What Is Web 2.0? Design Patterns and Business Models for the Next Generation of Software (2012)Geospatial big data handling theory and methods: A review and research challenges (2015)Social Sensing: A New Approach to Understanding Our Socioeconomic Environments (2015)Generating Models by the Expansion Method: Applications to Geographical Research* (1972)Estimation Methods for Models of Spatial Interaction (1975)The geography of parameter space: an investigation of spatial non-stationarity (1996)Methods to account for spatial autocorrelation in the analysis of species distributional data: a review (2007)An optimal parameters-based geographical detector model enhances geographic characteristics of explanatory variables for spatial heterogeneity analysis: cases with different types of spatial data (2020)An Introduction to Applied Geostatistics (1991)An Introduction to Applied Geostatistics. (1991)Geographically Weighted Regression: The Analysis of Spatially Varying Relationships (2002)GWmodel: an R Package for Exploring Spatial Heterogeneity using Geographically Weighted Models (2013)Annals of the American association of geographers (2016)Urban Green infrastructures: How much did they affect property prices in Singapore? (2022)A Computer Movie Simulating Urban Growth in the Detroit Region (1970)The limits to scale? Methodological reflections on scalar structuration (2001)A Route Map for Successful Applications of Geographically Weighted Regression (2022)Geographically Weighted Regression: A Natural Evolution of the Expansion Method for Spatial Data Analysis (1998)Computational improvements to multi-scale geographically weighted regression (2020)The 20-minute city: An equity analysis of Liverpool City Region (2021)Exploring differentiated impacts of socioeconomic factors and urban forms on city-level CO2 emissions in China: Spatial heterogeneity and varying importance levels (2022)Multicollinearity and correlation among local regression coefficients in geographically weighted regression (2005)A city of cities: Measuring how 15-minutes urban accessibility shapes human mobility in Barcelona (2021)Geographically and temporally weighted regression for modeling spatio-temporal variation in house prices (2010)Geographically and temporally neural network weighted regression for modeling spatiotemporal non-stationary relationships (2020)Spatial regression graph convolutional neural networks: A deep learning paradigm for spatial multivariate distributions (2021)Bikesharing in Europe, the Americas, and Asia (2010)Bike share’s impact on car use: Evidence from the United States, Great Britain, and Australia (2014)A geographically weighted regression model augmented by Geodetector analysis and principal component analysis for the spatial distribution of PM2.5 (2020)Accessibility to transit, by transit, and property prices: Spatially varying relationships (2020)Exploring the spatiotemporal patterns and correlates of urban vitality: Temporal and spatial heterogeneity (2023)Under the hood Issues in the specification and interpretation of spatial regression models (2002)Disaster related social media content processing for sustainable cities (2021)Sustainable design of running friendly streets: Environmental exposures predict runnability by Volunteered Geographic Information and multilevel model approaches (2022)Popularity influence mechanism of creative industry parks: A semantic analysis based on social media data (2023)Hedonic Prices and Implicit Markets: Product Differentiation in Pure Competition (1974)Introduction to Spatial Econometrics (2009)A deep learning approach for estimation of price determinants (2022)Predicting households’ residential mobility trajectories with geographically localized interpretable model-agnostic explanation (GLIME) (2023)Spatial machine learning for predicting physical inactivity prevalence from socioecological determinants in Chicago, Illinois, USA (2023)
this work references cited by second hop· second hop is a sample of the most-cited connections

References

  • 1996Geographically Weighted Regression: A Method for Exploring Spatial Nonstationarity3,678 cited
  • 2017Multiscale Geographically Weighted Regression (MGWR)1,461 cited
  • 2011Researching Volunteered Geographic Information: Spatial Data, Geographic Research, and New Social Practice864 cited
  • 2019mgwr: A Python Implementation of Multiscale Geographically Weighted Regression for Investigating Process Spatial Heterogeneity and Scale829 cited
  • 2019Inference in Multiscale Geographically Weighted Regression414 cited
  • 2020Geographically neural network weighted regression for the accurate estimation of spatial non-stationarity200 cited
  • 2010The Use of Geographically Weighted Regression for Spatial Prediction: An Evaluation of Models Using Simulated Data Sets191 cited
  • 2021A geographically weighted artificial neural network132 cited
  • 2020Exploring spatial variation of bike sharing trip production and attraction: A study based on Chicago’s Divvy system99 cited
  • 2020Social media semantic perceptions on Madrid Metro system: Using Twitter data to link complaints to space91 cited
  • 2020Measuring Bandwidth Uncertainty in Multiscale Geographically Weighted Regression Using Akaike Weights89 cited

Cited by

No citing works inside the corpus for this window.

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work