Climatization and Luminosity Optimization of Buildings using Genetic Algorithm, Random Forest and Regression Models - Trained Models

The proposed Random Forest is used to predict if the air conditioner and artificial lighting is to be turned on, if the motorized blinds are to be opened, and if the user should open the doors and/or windows of the room.  Regarding the Polynomial Regression, it is proposed two equations, one to predict the air conditioner temperature, and another to predict the artificial lighting luminosity.

File Description:

Input_Data_Means - Excel with the mean for each input data, required for the trained models

Polynomial_Regression_Air_Conditioner_Model - Trained polynomial regression air conditioner model

Polynomial_Regression_Air_Conditioner_Scaler - Trained polynomial regression air conditioner scaler

Polynomial_Regression_Artificial_Lighting_Model - Trained polynomial regression artificial lighting model

Polynomial_Regression_Artificial_Lighting_Scaler - Trained polynomial regression artificial lighting scaler

Random_Forest_Encoder - Trained random forest enconder

Random_Forest_Model - Trained random forest model