Difference between revisions of "Group06 Elec3city Proposal"
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* Transform Data for GWR model | * Transform Data for GWR model | ||
+ | * Users can use a histogram to check whether the variable is normally distributed | ||
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| 7. ||[[File:Elec3city dashboard 7.jpg|600 px]] || | | 7. ||[[File:Elec3city dashboard 7.jpg|600 px]] || | ||
* Select Variables for GWR model | * Select Variables for GWR model | ||
+ | * Users can remove correlated variables with the help of the correlation matrix plot | ||
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| 8. ||[[File:Elec3city dashboard 8.jpg|600 px]] || | | 8. ||[[File:Elec3city dashboard 8.jpg|600 px]] || |
Revision as of 11:59, 4 March 2019
Contents
Project Motivation
Climate change is a global environmental issue that impacts everyone, and a key contributor to this issue is the rising energy consumption to meet growing energy need. Singapore has launched campaigns to promote more efficient use of energy to meet this growing energy need rather than increasing energy consumption[1]. In order to better tackle this rising energy consumption, we will first need to understand what are the factors that contribute to this increase, and this was the key motivation that led us to embarking upon this project.
Project Objective
- Identify variables that have a strong influence on energy consumption. We plan to examine variables such as location in Singapore, temperature, age, income level and housing types
- Identify geographical clusters of sub-zones with abnormally high/low level of energy consumption in Singapore
- Identify the key difference between regions with high consumption and regions with low consumption
- Create a regression model that is able to predict the energy consumption of a family
Data
Literature Review
Methodology:
Learning Points:
Areas for improvement:
Approach
Techniques:
Web Application Design
Design Inspiration
The dashboard design is inspired by https://stanleyadion.shinyapps.io/AmazeingCrop
Initial Storyboard
Project Challenges
Key Challenges | Description | Solution | |
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1. | Technical Challenge | The proposed geovisualization including bivariate choropleth maps and box-plots by planning zones and dwelling type is complex. The group may encounter technical challenges such as finding relevant R packages and functions when building the visualization. |
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Project Timeline
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