A study on spatial analysis using R-based deep learning

Abstract

Deep learning is a rapidly growing technology repeating epoch-making development in the field of voice/text/image cognition. Its basic principle is to systematize information and let users find the pattern for themselves through the neural network using lots of layers. Technological core is anticipation by classification. This thesis uses SNS and webpage scrapping data and GIS data for consumer needs. Data will then be extracted by accurate classification for the purpose of spatial information data with deep learning algorithm. It is necessary to call shapefiles to R, improve the accessibility to data, and cross one data set to other data set areas. This thesis intends to analyze data of various environments with data analysis tool, R, and design the process combining data of spatial information and visualizing it based on deep learning algorithm. © 2016 SERSC.