Open AccessEvaluating the Significance of Financial Characteristics on Energy Consumption of Urban Building Stock using Principal Component Analysis and Logistic Regression
Author(s) -
V. Madhusudanan Pillai
Publication year - 2020
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.i1004.0799s20
Subject(s) - energy consumption , stock (firearms) , logistic regression , consumption (sociology) , urbanization , population , principal component analysis , regression analysis , environmental economics , business , econometrics , computer science , economics , engineering , economic growth , artificial intelligence , environmental health , machine learning , mechanical engineering , medicine , social science , sociology , electrical engineering
The increased population and the rapid urbanizationseek our attention towards sustainable production andconsumption in cities. In assessing the factors affecting the energyconsumption characteristics of the buildings, it is crucial that weconsider the user behavior along with the design characteristics ofthe buildings. One significant factor that influence the userbehavior is the financial characteristics. We use non-parametricmachine learning algorithms and econometric models to assessthe influence of the user behavior characteristics in the urbanbuilding stock in New York City. The analysis was conducted onthe open-data assessable, which is mandated by the Local Law 84.In our analysis we concluded that the financial characteristicshave a significant effect in the energy consumption of theresidential buildings, however, is not that significant in decidingthe energy consumption of the commercial buildings.