International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Volume XLII-3/W10
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W10, 975–979, 2020
https://doi.org/10.5194/isprs-archives-XLII-3-W10-975-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W10, 975–979, 2020
https://doi.org/10.5194/isprs-archives-XLII-3-W10-975-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  08 Feb 2020

08 Feb 2020

ANALYSIS OF THE LOCATION OF NANNING LARGE-SCALE MALL BASED ON BP NEURAL NETWORK

H. Huang1,2 and L. L. Liu1,2 H. Huang and L. L. Liu
  • 1College of Geomatic Engineering and Geoinfomatics, Gulin University of Technology, Gulin, 541004, China
  • 2Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin, 541004, China

Keywords: large-scale mall, geographic information system, matlab, location, BP neural network, Nanning City

Abstract. Site selection is a key first step in the operation of large-scale shopping malls, and most of the existing site selection methods lack practicality and efficiency. Therefore, it is necessary to carry out a scientific modeling of the site selection problem and provide effective reference information for site selection. With the development of machine learning algorithms, the modeling of such problems becomes more and more simple. In this paper, using matlab software as a tool, based on BP neural network algorithm, Nanning urban area is selected as the research object. After analyzing the influencing factors of location problem, the large-scale mall location analysis modeling is carried out. After repeated training and testing of the training data and the test data, the data for testing the usability is input into the model and applied for analysis. It turns out that the large-scale mall location analysis model is usable and can meet the site selection needs of the mall.