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 reasoningin 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.
| Original language | English |
|---|---|
| Title of host publication | Unknown Host Publication |
| Publisher | SciTePress |
| Number of pages | 8 |
| Publication status | Published (in print/issue) - 20 Sept 2013 |
| Event | 5th International Joint Conference on Computational Intelligence - Algarve, Portugal Duration: 20 Sept 2013 → … |
Conference
| Conference | 5th International Joint Conference on Computational Intelligence |
|---|---|
| Period | 20/09/13 → … |
