Nov 3, 2020 · The geographically weighed regression (GWR) method is used to realize the simulation of surface temperature based on the current date.
Oct 22, 2024 · (2021) utilized the Geographically Weighted Regression (GWR) method and a deep learning network model based on convolutional and LSTM to predict ...
A hybrid model integrating the geographically weighted regression (GWR) and deep neural network (DNN) was developed to estimate land surface temperature (LST).
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Sep 9, 2022 · A Novel Approach to Predicting Land Surface Temperature by the Combination of Geographically Weighted Regression and Deep Neural Network Models.
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The geographically weighed regression (GWR) method is used to realize the simulation of surface temperature based on the current date. The deep learning ...
Oct 22, 2024 · Scientists have used a geographically weighted regression to model the relationship between urban land surface temperature and land use ...
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Two regression models were used for statistical modeling and spatial analysis: Ordinary Least Squares (OLS) and Geographically Weighted Regression (GWR). In OLS ...
The results show that the gradient boosting model (GBM) machine learning algorithm is the most accurate in estimating LST. The albedo and NDVI are the surface ...
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Spatial downscaling of nighttime land surface temperature based on geographically neural network weighted regression kriging.
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Jan 25, 2024 · This research article proposes two forecasting techniques: Multiple Linear Regression (MLR) and Artificial Neural Network (ANN) models.