Comparative analysis of Recurrent and Finite Impulse Response Neural Networks in Time Series Prediction
Journal Title: Indian Journal of Computer Science and Engineering - Year 2012, Vol 3, Issue 1
Abstract
The purpose of this paper is to perform evaluation of two different neural network architectures used for solving temporal problems, i.e. time series prediction. The data sets in this project include Mackey-Glass, Sunspots, and Standard & Poor's 500, the stock market index. The study also presents a comparison study on the two networks and their performance.
Authors and Affiliations
Milos Miljanovic
Keywords
Related Articles
- EP ID EP119548
- DOI -
- Views 122
- Downloads 0
OPTIMAL IMPLEMENTATION METHODS FOR AUDIO CROSSTALK CANCELLATION ON DSP PROCESSORS
In general, frequency domain based techniques are preferred to time domain techniques for the implementation of audio crosstalk cancellation due to time domain techniques suffer from more computations. In this paper, the...
A hybrid approach based on EP and PSO for proficient solving of Unit Commitment Problem
Unit Commitment Problem (UCP) is a nonlinear mixed integer optimization problem used in the scheduling operation of power system generating units subjected to demand and reserve requirement constraints for achieving mini...
7TH CENTURY ANCIENT TAMIL CHARACTER RECOGNITION FROM TEMPLE WALL INSCRIPTIONS
Recognition of any ancient Tamil characters with respect to any language is complicated, since the ancient Tamil characters differ in written format, intensity, scale, style, and orientation, from person to person. Resea...
Performance Evolution of Various Wavelets in Cervical Lesion Detection
Cervical cancer is one of most common cancers among women in the world caused by human papilloma virus infection. It develops in the tissue of cervix which connects upper body of the uterus to the vagina. The types of ca...
TINY TCP/IP PROTOCOL SUITE FOR EMBEDDED SYSTEMS WITH 32 BIT MICROCONTROLLER
The scope of embedded devices is increasing day by day and the demand will be further more when networking technology is incorporated into these devices. Many embedded systems not only communicate with each other, but al...