ARTÍCULO
TITULO

Deriving prediction intervals for neuro-fuzzy networks

C. Mencar    
G. Castellano and A.M. Fanelli    

Resumen

No disponible

 Artículos similares

       
 
Stanley Förster, Michael Schultz and Hartmut Fricke    
The air traffic is mainly divided into en-route flight segments, arrival and departure segments inside the terminal maneuvering area, and ground operations at the airport. To support utilizing available capacity more efficiently, in our contribution we f... ver más
Revista: Aerospace

 
Jihwan Kim, Ung Jon and Hyeongcheol Lee    
In this paper, we propose an analytic solution of state-constrained optimal tracking control problems for continuous-time linear time-invariant (CT-LTI) systems that are based on model-based prediction, the quadratic penalty function, and the variational... ver más
Revista: Applied Sciences

 
Jae Yun Lee, Young Geun Yoon, Tae Keun Oh, Seunghee Park and Sang Il Ryu    
In the construction industry, it is difficult to predict occupational accidents because various accident characteristics arise simultaneously and organically in different types of work. Furthermore, even when analyzing occupational accident data, it is d... ver más
Revista: Applied Sciences

 
V. BRAHMANANDA RAO,K. HADA    
The feasibility of predicting spring rainfall over Rio Grande do Sul (Brazil) from the prior observations of SO index is examined. It is found that moderate success can be obtained. The optimum data period for deriving the prediction equations is abou... ver más
Revista: Atmósfera