The prediction of monthly average solar radiation with TDNN and ARIMA
In this paper, two well-known algorithms: ARIMA and TDNN (Time Delay Neural Network) are applied to conduct the short term prediction of solar radiation. For the daily solar radiation series is non-stable due to the fast weather changing, monthly average solar radiation is adopted as the data source...
Saved in:
Main Authors: | Wu, Ji., Chan, C. K. |
---|---|
Other Authors: | School of Electrical and Electronic Engineering |
Format: | Conference or Workshop Item |
Language: | English |
Published: |
2013
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/102836 http://hdl.handle.net/10220/16877 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Prediction of hourly solar radiation in Singapore
by: Er, Kah Chong
Published: (2012) -
Prediction of solar energy and radiation in Singapore
by: Lee, Jian Wei.
Published: (2010) -
Statistical and data mining approach for the prediction of solar radiation
by: Wu, Ji
Published: (2013) -
Forecasting of solar radiation using fuzzy neural networks
by: Seng, Anthony Sunjaya.
Published: (2012) -
Clustering of solar radiation
by: Ho, Chung.
Published: (2013)