A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Modelling and predicting energy consumption in laboratory buildings using multiple linear regression
This study was carried to improve the energy saving by investigating the influence factors that contribute to high energy consumption in a building particularly related to the building in Technology Campus, UTeM. Correlation analysis was performed to measure the strength of relationship between the influence factors whereby all the factors proven to have a strong linear correlation with the energy consumption. The Stepwise Selection of Multiple Linear Regression (MLR) were used to determine and modelling the most influence factors that affects the energy consumption. The final linear regression models was developed based on the amount of lighting in a building and surrounding temperature in the building which is considered as major influence factors that affect the energy consumption. Comparing the actual and predicted energy consumption in Technology Campus, UTeM showed that the MLR model obtained can be used to predict energy consumption and accounted for around 81% of the variance.
Modelling and predicting energy consumption in laboratory buildings using multiple linear regression
This study was carried to improve the energy saving by investigating the influence factors that contribute to high energy consumption in a building particularly related to the building in Technology Campus, UTeM. Correlation analysis was performed to measure the strength of relationship between the influence factors whereby all the factors proven to have a strong linear correlation with the energy consumption. The Stepwise Selection of Multiple Linear Regression (MLR) were used to determine and modelling the most influence factors that affects the energy consumption. The final linear regression models was developed based on the amount of lighting in a building and surrounding temperature in the building which is considered as major influence factors that affect the energy consumption. Comparing the actual and predicted energy consumption in Technology Campus, UTeM showed that the MLR model obtained can be used to predict energy consumption and accounted for around 81% of the variance.
Modelling and predicting energy consumption in laboratory buildings using multiple linear regression
Hussin, Nor Hafizah (author) / Aditya, Rahaini Mohd Said (author) / Ishak, Nadiah (author)
2021-04-15
doi:10.26555/konvergensi.v8i1.21531
Jurnal Ilmiah Matematika; Vol 8, No 1 (2021); 33-39 ; 2774-3241 ; 2087-8796
Article (Journal)
Electronic Resource
English
DDC:
690
Development of regression equations for predicting energy and hygrothermal performance of buildings
| Online Contents | 2008
Development of regression equations for predicting energy and hygrothermal performance of buildings
| Online Contents | 2008