Analysis on the relationships between the spatial distribution of primary care organizations and socio-demographic characteristics in a metropolitan city using the geographic weighted regression method

2013 ◽  
Vol 27 (2) ◽  
pp. 193-214
Author(s):  
이광수 ◽  
최영진
Keyword(s):  
Primary Care ◽  
Spatial Distribution ◽  
Regression Method ◽  
Demographic Characteristics ◽  
Weighted Regression ◽  
Metropolitan City ◽  
Geographic Weighted Regression ◽  
Weighted Regression Method

scholarly journals IMPROVED INDOOR POSITIONING TECHNIQUE BASED ON A GEOGRAPHIC WEIGHTED REGRESSION

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 441-446
Author(s):  
A. Gholami ◽  
P. Pahlavani ◽  
S. Azimi ◽  
S. Shakibi
Keyword(s):  
Genetic Algorithm ◽  
Access Point ◽  
Indoor Positioning ◽  
Regression Method ◽  
Weighted Regression ◽  
Position Determination ◽  
Access Points ◽  
Positioning Technique ◽  
Geographic Weighted Regression ◽  
Weighted Regression Method

Abstract. As technology and science develops and the coming of new equipment’s, standards and different waves spread. Each of these standards and technologies have involved in indoor positioning by various scholars. Various methods have been developed based on different systems, all of which are based on specific methods and concepts. The research tries to do indoor positioning using local Wi-Fi fingerprints and signals. To reduce the error to collect local fingerprints, RSS values are recorded in 4 directions and two times. Geographic weighted regression method has been used to train the network. In this research, a genetic algorithm is used to select the appropriate parameters. Ultimately, the accuracy of the model has reached 1.76 cm. The results show that the increase in the number of access points does not affect the accuracy of position determination, but the choice of the effective access point will be effective in reducing the error.

scholarly journals Weighted Regression Method for the Study of Pedestrian Flow Characteristics in Dhaka, Bangladesh

2013 ◽  
Vol 7 (4) ◽  
Author(s):  
Khalidur Rahman ◽  
Noraida Abdul Ghani ◽  
Anton Abdulbasah Kamil ◽  
Adli Mustafa
Keyword(s):  
Flow Characteristics ◽  
Regression Method ◽  
Weighted Regression ◽  
Pedestrian Flow ◽  
Weighted Regression Method

scholarly journals Geographically weighted regression: Method for analysing spatial nonstationarity of geographical phenomenon

Geografie ◽  
2008 ◽  
Vol 113 (2) ◽  
pp. 125-139 ◽  
Author(s):  
Pavlína Spurná
Keyword(s):  
Linear Regression ◽  
Geographically Weighted Regression ◽  
Quantitative Method ◽  
Regression Method ◽  
Weighted Regression ◽  
Parliamentary Election ◽  
Voting Behaviour ◽  
Significant Difference ◽  
Spatial Nonstationarity ◽  
Weighted Regression Method

The article deals with one of the new quantitative method used in geography, geographically weighted regression (GWR). This method is based on the premise that relationships between variables might not be constant across the study area and explores this phenomenon called spatial non-stationarity. Using the GWR technique to study voting behaviour in Czechia in the parliamentary election in 2002, it is evident that there is a significant difference between the linear regression and GWR models. The examples highlight the relevance and usefulness of GWR and show how it can improve geographical research and potentially also our understanding of geographical processes.

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