Difference between revisions of "Qui Vivra Verra - Technology"
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| − | <div style="background: #dce6f9; line-height: 0.3em; font-family:Century Gothic; border-left: #003464 solid 15px;"><div style="border-left: #FFFFFF solid 5px; padding:15px;font-size:15px;"><font color= "#000000"><strong>Apache Spark | + | <div style="background: #dce6f9; line-height: 0.3em; font-family:Century Gothic; border-left: #003464 solid 15px;"><div style="border-left: #FFFFFF solid 5px; padding:15px;font-size:15px;"><font color= "#000000"><strong>SQLite and SpatiaLite</strong></font></div></div> |
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| + | SQLite and SpatiaLite extension will be used as a database to store the geospatial data uploaded by the user. SpatiaLite will then be used to query from the database variables needed for the huff’s model. | ||
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| + | <div style="background: #dce6f9; line-height: 0.3em; font-family:Century Gothic; border-left: #003464 solid 15px;"><div style="border-left: #FFFFFF solid 5px; padding:15px;font-size:15px;"><font color= "#000000"><strong>Apache Spark</strong></font></div></div> | ||
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| + | We will be using Apache Spark’s Machine Learning Library for performing regression analysis on the huff’s model. | ||
Revision as of 22:31, 31 August 2016
JMP Pro 12 is a tool developed by the JMP division of SAS. As the data files are too large to be opened by conventional means such as Excel and Notepad, we will be using this tool to explore the data. Market Segment Analysis will also be done using the clustering function of this application.
Leaflet.js is an open source javascript library for interactive maps. This tool will be used to create a visualization page for the users where a map of Singapore, as well as point symbols representing various facilities will be displayed. The user can select the attribute to be considered for computing the attractiveness index by selecting or deselecting facility layers as well as varying buffer radius. This tool is selected as it provides a range of interactive maps and is easy to implement. It supports various plugins to extend its functionality.
JavaScript is a coding language for the web. We will be using JavaScript for most of the application’s user interfaces as it allows the implementation of various libraries to support user’s interactions and improve visualisation.
Turf.js was mainly used for spatial analysis. It provides the functionality to analyse, aggregate and transform data into GeoJSON.
SQLite and SpatiaLite extension will be used as a database to store the geospatial data uploaded by the user. SpatiaLite will then be used to query from the database variables needed for the huff’s model.
We will be using Apache Spark’s Machine Learning Library for performing regression analysis on the huff’s model.
