DocumentCode
2254463
Title
Can we estimate atmospheric predictability by performance of neural network forecasting? the toy case studies of unforced and forced lorenz models
Author
Pasini, Antonello ; Pelino, Vinicio
fYear
2005
fDate
20-22 July 2005
Firstpage
69
Lastpage
74
Keywords
Air pollution; Atmosphere; Atmospheric modeling; Chaos; Computer aided software engineering; Electronic mail; Frequency; Neural networks; Predictive models; Remuneration;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence for Measurement Systems and Applications, 2005. CIMSA. 2005 IEEE International Conference on
Print_ISBN
0-7803-9026-1
Type
conf
DOI
10.1109/CIMSA.2005.1522829
Filename
1522829
Link To Document