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An FCM modeling for using a priori knowledge: application study in modeling quadruped walking

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Abstract

Fuzzy cognitive map (FCM) is well established as a decision-making mechanism with many applications. This paper presents a new strategy for realistic FCM-based inference named input-sensitive FCM. The problem of lack of influence from initial concepts’ weights or priory knowledge on decision outputs is resolved. The results and comparisons with the existing inference models are included to evaluate the strength of the new strategy. The quadruped walking cycle is simulated as a case study for sanity testing and validation of the developed model in terms of realistic decision outputs.

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Authors and Affiliations

  1. Institute of Advanced Technology, University Putra Malaysia, 43400, Serdang, Selangor, Malaysia

    O. Motlagh, S. H. Tang, A. R. Ramli & D. Nakhaeinia

Authors
  1. O. Motlagh
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  2. S. H. Tang
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  3. A. R. Ramli
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  4. D. Nakhaeinia
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Corresponding author

Correspondence to O. Motlagh.

Appendix

Appendix

The random matrix of events used for Figs. 3 and 4:

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Motlagh, O., Tang, S.H., Ramli, A.R. et al. An FCM modeling for using a priori knowledge: application study in modeling quadruped walking. Neural Comput & Applic 21, 1007–1015 (2012). https://doi.org/10.1007/s00521-010-0510-5

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  • DOI: https://doi.org/10.1007/s00521-010-0510-5

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