4. Conclusion

This chapter provides a comprehensive literature review to demonstrate the application of pattern recognition and machine learning techniques for solar radiation forecasting. The results of this survey show that identifying the irregular patterns of solar radiation time series by data clustering and/or classification provides better training for neural networks and enhances the forecast accuracy. However, computational complexities of hybrid forecasting methods utilizing multiple pattern recognition and machine learning techniques render their applications inefficient for online predictions or very short-term forecasting.
