Ideal Utility Project
Landry Lab Member, August- Dec, 2011
I developed statistical tracking and prediction models using statistical regression for efficient energy modeling and prediction for different cities for one of the leading restaurant industry chain. The project involved defining precise factors among restaurants that affect energy consumption and analyzing their interactions with each other. The models were designed and tested on real data with high accuracy (majority of the variance in the data was explained). The end result of the project was a detailed analysis on both tracking and prediction models and recommendations for the client for energy reduction. I presented this work in the Industrial Engineering Graduate Research Symposium, 2014 in poster format.