Simulation Of Air Conditioning System For Thermal Comfort Using Machine Learning techniques
2022-26-1229
05/26/2022
- Event
- Content
- This study is about the system which establishes a model for environmental factors such as temperature, humidity, and air velocity of thermal comfort indicators by implementing different Machine Learning technique. In this work the principal goal is analyzing air flow, distribution of temperature and pressure in the Living room. In order to achieve the goal the domain is consider which is divided in to discretized manner which will be further used to record the thermal sensation and airflow. For the same simulated environment the experiment will be conducted, which resulting in to forming the dataset with respect time, relative humidity, draft, temperature, air flow. By considering the recorded dataset, machine learning algorithm like SVM (Support Vector Machine), radial basis function for different kernels, Decision tree, XG Boost and Adaboost are used to create the model in Pythan. Finally, various performance metrics like accuracy, sensitivity and specificity for all techniques are calculated and compared with one another.
- Citation
- Shete, P., raut, v., Mandhare, J., Borgaonkar, A. et al., "Simulation Of Air Conditioning System For Thermal Comfort Using Machine Learning techniques," SAE Technical Paper 2022-26-1229, 2022, .