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

The Research of Indoor Positioning Based on Double Wireless Access Points

2014 ◽  
Vol 536-537 ◽  
pp. 291-295
Author(s):  
Ke Fei Cheng ◽  
Hong Cai
Keyword(s):  
Access Point ◽  
Signal Propagation ◽  
Indoor Positioning ◽  
Propagation Model ◽  
Wireless Access ◽  
Average Error ◽  
Manifold Regularization ◽  
Access Points ◽  
Signal Propagation Model ◽  
Wireless Access Point

Aiming at the problem of low accuracy of indoor positioning by singular wireless access point, this paper proposes a method which is based on the result of weighted calculation using the positioning of two wireless access points. In the experiment, the method use two wireless access point to acquire the signal samples respectively in an office, using the signal propagation model and manifold regularization model to study the surroundings. At the positioning phase, the final position can be obtained by weighted calculating the results of the two wireless access point and the nature of triangular midline. The experimental results show that using the proposed method, the average error value is 20% lower than the corresponding version, using singular wireless access point.

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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