Autonomous Data Density pruning fuzzy neural network for Optical Interconnection Network

de Campos Souza, Paulo Vitor and Soares, Eduardo A. and Guimarães, Augusto Junio and Araujo, Vanessa Souza and Araujo, Vinicius Jonathan S. and Rezende, Thiago Silva (2021) Autonomous Data Density pruning fuzzy neural network for Optical Interconnection Network. Evolving Systems, 12 (4). pp. 899-911. ISSN 1868-6478

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Abstract

Traditionally, fuzzy neural networks have parametric clustering methods based on equally spaced membership functions to fuzzify inputs of the model. In this sense, it produces an excessive number calculations for the parameters’ definition of the network architecture, which may be a problem especially for real-time large-scale tasks. Therefore, this paper proposes a new model that uses a non-parametric technique for the fuzzification process. The proposed model uses an autonomous data density approach in a pruned fuzzy neural network, wich favours the compactness of the model. The performance of the proposed approach is evaluated through the usage of databases related to the Optical Interconnection Network. Finally, binary patterns classification tests for the identification of temporal distribution (asynchronous or client–server) were performed and compared with state-of-the-art fuzzy neural-based and traditional machine learning approaches. Results demonstrated that the proposed model is an efficient tool for these challenging classification tasks.

Item Type:
Journal Article
Journal or Publication Title:
Evolving Systems
Additional Information:
The final publication is available at Springer via http://dx.doi.org/10.1007/s12530-020-09336-3
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2200/2207
Subjects:
?? autonomous data densityfuzzy neural networksoptical interconnection networkcontrol and systems engineeringmodelling and simulationcomputer science applicationscontrol and optimization ??
ID Code:
144545
Deposited By:
Deposited On:
20 Aug 2020 15:40
Refereed?:
Yes
Published?:
Published
Last Modified:
03 Nov 2024 01:18