Principles of data mining
A data mining application on air temperature database
ADVIS'04 Proceedings of the Third international conference on Advances in Information Systems
SunCast: fine-grained prediction of natural sunlight levels for improved daylight harvesting
Proceedings of the 11th international conference on Information Processing in Sensor Networks
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Statistical approach is often used in time series analysis. One of its uses is to predict the future trend of a time series. This can be applied in many applications such as solar radiation, economics and other researches related to time series. In this paper, we use several classic statistical models to fit the solar radiation time series. The goal is to find a suitable radiation model in predicting the trend of solar radiation time series. The simulation result shows that Linear Regression has better performance than other models such as the Auto Regression, Auto Regression Integrate Moving Average. The Linear Regression method requires a number of previous data for prediction. Simulation shows that a list of 10 to 15 past data values yields optimal result.