IS424 Data Mining and Analytics Project

Project Overview

Electricity consumption predictor that predicts electrcity consumption (kWh) for the specified month based on weather, region, and dwelling type inputs. Prediction models include 8 Deep Neural Nets, 7 Regression models, 3 Ensemble models and 1 K-Nearest Neighbors model

Datasets - (found in "python notebooks")

Singapore Energy Statistics

• Gathered by the Energy Market Authority of Singapore
• Variables used from Sheet T3.5 - Average Monthly Household Elecrtricity Consumption by Planning Area & Dwelling Type

Singapore weather dataset

• Historical climate data gathered by the Meteorological Service of Singapore
• Data scraped using a script
• Variables used [grouped by location]:
  • Daily rainfall
  • Highest 120m rainfall
  • Temperature (Mean, Maximum, Minimum)
  • Wind speed (Mean, Maximum)

Running the application

Install the dependencies with the command below.

pip install -r requirements.txt

Finally, run the program with the command below.

python app.py