Nonlinear Modeling for Time Series Based on the Genetic Programming and its Applications

2006 ◽  
Author(s):  
Jian-jun Lu ◽  
Yun-ling Liu ◽  
Shozo Tokinaga
Keyword(s):  
Time Series ◽  
Genetic Programming ◽  
Nonlinear Modeling

scholarly journals Time series prediction using a recursive algorithm of a combination of genetic programming and constant optimization

2002 ◽  
Vol 15 (2) ◽  
pp. 265-279 ◽  
Author(s):  
Witthaya Panyaworayan ◽  
Georg Wuetschner
Keyword(s):  
Time Series ◽  
Genetic Programming ◽  
Recursive Algorithm ◽  
Time Series Prediction ◽  
Prediction Function ◽  
Prediction Functions

In this paper we present a prediction process of Time Series using a combination of Genetic Programming and Constant Optimization. The Genetic Programming will be used to evolve the structure of the prediction function, whereas the Constant Optimization will determine the numerical parameters of the prediction function. The prediction process is applied recursively. In each recursion step, a sub-prediction function is evolved. At the end of the iteration all sub-prediction functions form the final prediction function. The avoiding of a major problem in the prediction called over-fitting is also described in this article.

Using Genetic Programming to Extract Knowledge from Artificial Neural Networks

2008 ◽  
pp. 308-327
Author(s):  
Daniel Rivero ◽  
Miguel Varela ◽  
Javier Pereira
Keyword(s):  
Neural Networks ◽  
Time Series ◽  
Artificial Neural Networks ◽  
Genetic Programming ◽  
Recurrent Neural Networks ◽  
Know How ◽  
Artificial Neural

A technique is described in this chapter that makes it possible to extract the knowledge held by previously trained artificial neural networks. This makes it possible for them to be used in a number of areas (such as medicine) where it is necessary to know how they work, as well as having a network that functions. This chapter explains how to carry out this process to extract knowledge, defined as rules. Special emphasis is placed on extracting knowledge from recurrent neural networks, in particular when applied in predicting time series.

Sign in / Sign up

Export Citation Format

Share Document