Dynamically Reconfigurable Online Self-organising Fuzzy Neural Network with Variable Number of Inputs for Smart Home Application

Anjan Kumar Ray, Gang Leng, T. M. Mcginnity, Sonya Coleman, Liam Maguire

2013

Abstract

A self-organising fuzzy-neural network (SOFNN) adapts its structure based on variations of the input data. Conventionally in such self-organising networks, the number of inputs providing the data is fixed. In this paper, we consider the situation where the number of inputs to a network changes dynamically during its online operation. We extend our existing work on a SOFNN such that the SOFNN can self-organise its structure based not only on its input data, but also according to the changes in the number of its inputs. We apply the approach to a smart home application, where there are certain situations when some of the existing events may be removed or new events emerge, and illustrate that our approach enhances cognitive reasoning in a dynamic smart home environment. In this case, the network identifies the removed and/or added events from the received information over time, and reconfigures its structure dynamically. We present results for different combinations of training and testing phases of the dynamic reconfigurable SOFNN using a set of realistic synthesized data. The results show the potential of the proposed method.

Paper Citation

in Harvard Style

Kumar Ray A., Leng G., M. Mcginnity T., Coleman S. and Maguire L. (2013). Dynamically Reconfigurable Online Self-organising Fuzzy Neural Network with Variable Number of Inputs for Smart Home Application . In Proceedings of the 5th International Joint Conference on Computational Intelligence - Volume 1: NCTA, (IJCCI 2013) ISBN 978-989-8565-77-8, pages 507-514. DOI: 10.5220/0004555405070514

in Bibtex Style

@conference{ncta13,
author={Anjan Kumar Ray and Gang Leng and T. M. Mcginnity and Sonya Coleman and Liam Maguire},
title={Dynamically Reconfigurable Online Self-organising Fuzzy Neural Network with Variable Number of Inputs for Smart Home Application},
booktitle={Proceedings of the 5th International Joint Conference on Computational Intelligence - Volume 1: NCTA, (IJCCI 2013)},
year={2013},
pages={507-514},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004555405070514},
isbn={978-989-8565-77-8},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 5th International Joint Conference on Computational Intelligence - Volume 1: NCTA, (IJCCI 2013)
TI - Dynamically Reconfigurable Online Self-organising Fuzzy Neural Network with Variable Number of Inputs for Smart Home Application
SN - 978-989-8565-77-8
AU - Kumar Ray A.
AU - Leng G.
AU - M. Mcginnity T.
AU - Coleman S.
AU - Maguire L.
PY - 2013
SP - 507
EP - 514
DO - 10.5220/0004555405070514