Journal
INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL
Volume 14, Issue 6, Pages 653-669Publisher
CCC PUBL-AGORA UNIV
DOI: 10.15837/ijccc.2019.6.3692
Keywords
fuzzy cognitive Map (FCM); inference simulation; artificial intelligent system; dynamic scenario analysis; IQ Test; linguistic analysis
Funding
- Chinese Academy of Sciences [460806-0009]
- Graduate Research and Creative Activity (GRACA) [42-1209-9116]
- University of Nebraska at Omaha
- National Science Foundation of China [7193000078, 91546201]
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This research article uses a Fuzzy Cognitive Map (FCM) approach to improve an earlier proposed IQ test characteristics of Artificial Intelligence (AI) systems. The defuzzification process makes use of fuzzy logic and the triangular membership function along with linguistic term analyses. Each edge of the proposed FCM is assigned to a positive or negative influence type associated with a quantitative weight. All the weights are based on the defuzzified value in the defuzzification results. This research also leverages a dynamic scenario analysis to investigate the interrelationships between driver concepts and other concepts. Worst and best-case scenarios have been conducted on the correlation among concepts. We also use an inference simulation to examine the concepts importance order and the FCM convergence status. The analysis results not only examine the FCM complexity, but also draws insightful conclusions.
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