|
Activity Number:
|
549
|
|
Type:
|
Topic Contributed
|
|
Date/Time:
|
Thursday, August 6, 2009 : 8:30 AM to 10:20 AM
|
|
Sponsor:
|
Section on Risk Analysis
|
| Abstract - #305894 |
|
Title:
|
Neural Networks: A Flexible Nonlinear Model
|
|
Author(s):
|
Barbara Bailey*+
|
|
Companies:
|
San Diego State University
|
|
Address:
|
, , ,
|
|
Keywords:
|
|
|
Abstract:
|
Many environmental processes evolve over time and space creating a complex dynamical system. The construction of nonlinear regression models that describe the evolution of complex processes will be useful in many applications. A feed-forward neural network is used as a flexible nonlinear model and can be used to estimate interesting dynamical systems quantities, as well as prediction. Statistical properties of the neural network model are investigated, including construction of confidence and prediction intervals. Dynamical Systems of interest will include noisy data generated from nonlinear differential equations and the abundance of Calanus finmarchicus from hydrographic data.
|
- The address information is for the authors that have a + after their name.
- Authors who are presenting talks have a * after their name.
Back to the full JSM 2009 program |
