1. Intelligent Database Systems Lab Presenter : Fen-Rou Ciou Authors : Hamdy K. Elminir, Yosry A. Azzam, Farag I. Younes 2007,ENERGY Prediction of hourly and daily diffuse fraction using neural network, as compared to linear regression models

2. Intelligent Database Systems Lab Outlines Motivation Objectives Methodology Experiments Conclusions Comments

3. Intelligent Database Systems Lab Motivation For most of the locations all over Egypt the records of diffuse radiation in whatever scale are non-existent. In case that it exists, the quality of these records is not as good as it should be for most purposes and so an estimate of its values is desirable.

4. Intelligent Database Systems Lab Objectives To achieve such a task, an artificial neural network (ANN) model has been proposed to predict diffuse fraction (K D ) in hourly and daily scale.

5. Intelligent Database Systems Lab Methodology

6. Intelligent Database Systems Lab Methodology It can predict the K D value in hourly and daily scales base on K T and S / S 0 In hourly scale, the input layer has five individual inputs. In daily scale, the input layer has three input.

7. Intelligent Database Systems Lab Experiments– In hourly scale

8. Intelligent Database Systems Lab Experiments– In hourly scale

9. Intelligent Database Systems Lab Experiments – In daily scale Gopinathan and Solar’s Model ANN’s Model

10. Intelligent Database Systems Lab Experiments – In daily scale Gopinathan and Solar’s Model ANN’s Model

11. Intelligent Database Systems Lab Conclusions These findings show that the neural network is more suitable to predict diffuse fraction than the proposed regression models at least for the Egyptian sites.

12. Intelligent Database Systems Lab Comments Advantages – Let me relearn statistics. Applications – Prediction diffuse fraction