This is a report about machine learning in the field of computer science. The problem handled is prediction of energy consumption in district heating systems. Prediction of energy consumption in district heating systems is a delicate problem because of the social behaviours, weather and distribution time that has to be accounted for. One algorithm is introduced and three different experiments are made to determine if the algorithm is useful. The results from the experiments were good. This report differs in approach to the problem then other reports found in this field. The difference is that this report tries to handle social behaviours and looks at a decentralized view of the problem instead of centralized.Denna rapport är om maskininlärn...
Now the world is becoming more sophisticated and networked, and a massive amount of data is being ge...
The growing population in cities increases the energy demand and affects the environment by increasi...
District heating is widely used in cold countries and it is a way of maintaining centralised heating...
Although Sweden's geographical location entails a relatively low outdoor temperature for much of the...
The purpose of this study is to investigate if it is possible to decrease Sweden's energy consumptio...
Machine learning algorithms can be used to predict the future demand for heat in buildings. This can...
In an increasingly applied domain of pervasive computing, sensing devices are being deployed progres...
The district heating (DH) industry is facing an important transformation towards more efficient netw...
The purpose of this study is to investigate if it is possible to decrease Sweden's energy consumptio...
A method for predicting consumer heat power usage was examined, for the purpose of implementing such...
In recent years, Machine Learning has become one of the most used techniques when modelling relation...
Indoor climate control is responsible for a substantial amount of the world's total energy expenditu...
This thesis discusses the district heating demand forecasting. For the production planning of the en...
This paper describes an evaluation of five machine learning algorithms for predicting the domestic s...
This report aims to examine the use and development of a more intelligent heating process in a house...
Now the world is becoming more sophisticated and networked, and a massive amount of data is being ge...
The growing population in cities increases the energy demand and affects the environment by increasi...
District heating is widely used in cold countries and it is a way of maintaining centralised heating...
Although Sweden's geographical location entails a relatively low outdoor temperature for much of the...
The purpose of this study is to investigate if it is possible to decrease Sweden's energy consumptio...
Machine learning algorithms can be used to predict the future demand for heat in buildings. This can...
In an increasingly applied domain of pervasive computing, sensing devices are being deployed progres...
The district heating (DH) industry is facing an important transformation towards more efficient netw...
The purpose of this study is to investigate if it is possible to decrease Sweden's energy consumptio...
A method for predicting consumer heat power usage was examined, for the purpose of implementing such...
In recent years, Machine Learning has become one of the most used techniques when modelling relation...
Indoor climate control is responsible for a substantial amount of the world's total energy expenditu...
This thesis discusses the district heating demand forecasting. For the production planning of the en...
This paper describes an evaluation of five machine learning algorithms for predicting the domestic s...
This report aims to examine the use and development of a more intelligent heating process in a house...
Now the world is becoming more sophisticated and networked, and a massive amount of data is being ge...
The growing population in cities increases the energy demand and affects the environment by increasi...
District heating is widely used in cold countries and it is a way of maintaining centralised heating...