Temperature Forecast in Buildings Using Machine Learning Techniques
نویسندگان
چکیده
Energy efficiency in buildings requires having good prediction of the variables that define the power consumption in the building. Temperature is the most relevant of these variables because it affects the operation of the cooling systems in summer and the heating systems in winter, while being also the main variable that defines comfort. This paper presents the application of classical methods of time series forecasting, such as Autoregressive (AR), Multiple Linear Regression (MLR) and Robust MLR (RMLR) models, along with others derived from more complex machine learning techniques, including Multilayer Perceptron with Non-linear Autoregressive Exogenous (MLP-NARX) and Extreme Learning Machine (ELM), to forecast temperature in buildings. The results obtained in the temperature prediction of several rooms of a building show the goodness of machine learning methods as compared to traditional approaches.
منابع مشابه
Machine Learning Techniques for Short-Term Electric Power Demand Prediction
Since several years ago, power consumption forecast has attracted considerable attention from the scientific community. Although there exist several works that deal with this issue, it remains open. The good management of energy consumption in HVAC (Heating, Ventilation and Air Conditioning) systems for large households and public buildings may benefit from a sustainable development in terms of...
متن کاملMachine learning algorithms in air quality modeling
Modern studies in the field of environment science and engineering show that deterministic models struggle to capture the relationship between the concentration of atmospheric pollutants and their emission sources. The recent advances in statistical modeling based on machine learning approaches have emerged as solution to tackle these issues. It is a fact that, input variable type largely affec...
متن کاملFault Detection of Anti-friction Bearing using Ensemble Machine Learning Methods
Anti-Friction Bearing (AFB) is a very important machine component and its unscheduled failure leads to cause of malfunction in wide range of rotating machinery which results in unexpected downtime and economic loss. In this paper, ensemble machine learning techniques are demonstrated for the detection of different AFB faults. Initially, statistical features were extracted from temporal vibratio...
متن کاملUsing Machine Learning Algorithms for Automatic Cyber Bullying Detection in Arabic Social Media
Social media allows people interact to express their thoughts or feelings about different subjects. However, some of users may write offensive twits to other via social media which known as cyber bullying. Successful prevention depends on automatically detecting malicious messages. Automatic detection of bullying in the text of social media by analyzing the text "twits" via one of the machine l...
متن کاملModeling of Chloride Ion Separation by Nanofiltration Using Machine Learning Techniques
In this work, several machine learning techniques are presented for nanofiltration modeling. According to the results, specific errors are defined. The rejection due to Nanofiltration increases with pressure but decreases with increasing the concentration of chloride ion. Methods of machine learning represent the rejection of nanofiltration as a function of concentration, pH, pressure and also ...
متن کامل