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Authors: Anjan Kumar Ray ; Gang Leng ; T. M. Mcginnity ; Sonya Coleman and Liam Maguire

Affiliation: University of Ulster, United Kingdom

Keyword(s): Self-organising System, Fuzzy Logic, Neural Network, Cognitive Reasoning.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Computational Intelligence ; Health Engineering and Technology Applications ; Higher Level Artificial Neural Network Based Intelligent Systems ; Human-Computer Interaction ; Learning Paradigms and Algorithms ; Methodologies and Methods ; Neural Networks ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Self-Organization and Emergence ; Sensor Networks ; Signal Processing ; Soft Computing ; Theory and Methods

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 te sting phases of the dynamic reconfigurable SOFNN using a set of realistic synthesized data. The results show the potential of the proposed method. (More)

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Paper citation in several formats:
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 (IJCCI 2013) - NCTA; ISBN 978-989-8565-77-8; ISSN 2184-3236, SciTePress, pages 507-514. DOI: 10.5220/0004555405070514

@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 (IJCCI 2013) - NCTA},
year={2013},
pages={507-514},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004555405070514},
isbn={978-989-8565-77-8},
issn={2184-3236},
}

TY - CONF

JO - Proceedings of the 5th International Joint Conference on Computational Intelligence (IJCCI 2013) - NCTA
TI - Dynamically Reconfigurable Online Self-organising Fuzzy Neural Network with Variable Number of Inputs for Smart Home Application
SN - 978-989-8565-77-8
IS - 2184-3236
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
PB - SciTePress