Dendritic cell algorithm with fuzzy inference system for input signal generation

Noe Elisa, Jie Li, Zheming Zuo, Longzhi Yang*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

14 Citations (Scopus)
19 Downloads (Pure)

Abstract

Dendritic cell algorithm (DCA) is a binary classification system developed by abstracting the biological danger theory and the functioning of human dendritic cells. The DCA takes three signals as inputs, including danger, safe and pathogenic associated molecular pattern (PAMP), which are generated in its pre-processing and initialization phase. In particular, after a feature selection process for a given training data set, each selected attribute is assigned to one of the three input signals. Then, these input signals are calculated as the aggregation of their associated features, usually implemented by a simple average function followed by a normalisation process. If a nonlinear relationship exists between a signal and its corresponding selected attributes, the resulting signal using the average function may negatively affect the classification results of the DCA. This work proposes an approach named TSK-DCA to address such limitation by aggregating the assigned features of a signal linearly or non-linearly depending on their inherit relationship using the TSK+ fuzzy inference system. The proposed approach was evaluated and validated using the popular KDD99 data set, and the experimental results indicate the superiority of the proposed approach compared to its conventional counterpart.

Original languageEnglish
Title of host publicationAdvances in Computational Intelligence Systems
Subtitle of host publicationContributions Presented at the 18th UK Workshop on Computational Intelligence, 2018
EditorsAhmad Lotfi, Hamid Bouchachia, Alexander Gegov, Caroline Langensiepen, Martin McGinnity
PublisherSpringer
Pages203-214
Number of pages12
ISBN (Electronic)9783319979823
ISBN (Print)9783319979816
DOIs
Publication statusE-pub ahead of print - 11 Aug 2018
Event18th UK Workshop on Computational Intelligence, UKCI 2018 - Nottingham, United Kingdom
Duration: 5 Sep 20187 Sep 2018

Publication series

NameAdvances in Intelligent Systems and Computing
Volume840
ISSN (Print)2194-5357

Conference

Conference18th UK Workshop on Computational Intelligence, UKCI 2018
CountryUnited Kingdom
CityNottingham
Period5/09/187/09/18

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