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.

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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