Data analysis technique to extract threshold value for Fuzzy Inference System in classifying malicious agents
This paper describes a data analysis technique used to extract threshold values of a Fuzzy Inference System's (FIS) inputs. In this work, the FIS is used to classify malicious agents' behaviour in a Multi-Agent System (MAS) environment. The extraction of suitable FIS inputs threshold value...
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| 主要な著者: | , , , |
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| フォーマット: | Conference Paper |
| 言語: | English |
| 出版事項: |
2017
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| タグ: |
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| 要約: | This paper describes a data analysis technique used to extract threshold values of a Fuzzy Inference System's (FIS) inputs. In this work, the FIS is used to classify malicious agents' behaviour in a Multi-Agent System (MAS) environment. The extraction of suitable FIS inputs threshold values in the MAS environment are based on data analysis derived from several simulation runs. Subsequently, the extracted threshold values are applied in the rules of the FIS framework for classifying malicious agents' behaviors. Results indicated that extracting the fuzzy threshold values using the data analysis technique is an acceptable alternative method when no domain expert is available. © 2014 IEEE. |
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