… sixth census data and geographic information data of various … map analysis to analyze the
spatial distribution and spatial … regression model, spatial lag model and spatial error model …

… forms from its 80,000 population, we will examine spatial factors affecting submission rate …
regression model with district dummy variables and GWR (geographically weighted regression…

… Some research has offered supportive spatial strategies, such … via analyses on touristic
resources, population and economic … analysis), network analysis method, spatial regression …

… analysis shows that: As long as the population of samples meet the requirement of model
calculation (for example: 5%), the Pan-CPI model … coarse spatial resolution time series data is …

… regression model was used to select features and develop radiomics signature, subjective
image features model, and combined diagnostic model… and grayscale spatial distribution of …

… Abstract Given the rapid rise in human population and increasing urbanization, it is important
to … According to the regression model of the relationship between species and functional …

… Likely, one key role is the major economic and demographic … In short, using regression
analysis, this study looks at the … method known as spatial autocorrelation regression (SAR). The …

… spatial model which … population, by the time that we come to use the discriminant function.
We might choose the training set to be data for the first six months, and the test set to be data …

… Covering an area of approximately 16,410 km2, Beijing has a permanent resident population
of 21.89 million by 2020, 1,050 parks of various types, and a total park green space area of …

… Data can be represented as visual sampling points in the space and then be cultivated to form
the population … Based on their relationship, concept generation and causality analysis can …