Cart (Loading....) | Create Account
Close category search window
 

A novel shape based batching and prediction approach for sunspot data using HMMs and ANNs

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Bhardwaj, S. ; Dept. of Instrum. of Control Eng., Netaji Subhas Inst. of Technol. (NSIT), New Delhi, India ; Srivastava, S. ; Gupta, J.R.P. ; Madhvan, A.

This paper introduces a novel approach which uses a Hidden Markov Model (HMM) based Artificial Neural Networks (ANN) for prediction of systems that are non deterministic, dynamical and chaotic in nature. The HMM is used for shape based batch creation of training data, which is then processed one batch at a time by an ANN. The weights and Learning Rate of the ANN are tweaked to predict the correct output for an input dataset. The novel Prediction method used here exploits the Pattern Identification prowess of the HMM for batch selection and the ANNs of each batch to predict the output of the system. The Standard application of the Sun-Spot Data (SSD) was used for testing the competence of this method.

Published in:

Power Electronics (IICPE), 2010 India International Conference on

Date of Conference:

28-30 Jan. 2011

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.