Preview

Proceedings of Telecommunication Universities

Advanced search

Method for Validating Graph Models Based on the Effective Control Algorithm

https://doi.org/10.31854/1813-324X-2020-6-3-58-65

Abstract

The article proposes a method for validating mathematical models represented by oriented weighted signed graphs using an efficient control algorithm. The method considers the validated model in terms of spectral properties of the graph adjacency matrix represented by a fuzzy cognitive map (FCM). Using an efficient control algorithm, you can determine the eigenvector direction of the adjacency matrix. This property defines the criteria for checking the FCM.

About the Authors

V. .. Vasiliev
Institute of Computer Technologies and Information Safety of Southern Federal Universit
Russian Federation


A. .. Tselykh
Institute of Computer Technologies and Information Safety of Southern Federal Universit
Russian Federation


L. .. Tselykh
Taganrog Institute named after A.P. Chekhov (branch) of Rostov State University of Economics
Russian Federation


References

1. Kosko B. Fuzzy cognitive maps // International Journal of Man-Machine Studies. 1986. Vol. 24. Iss. 1. PP. 65-75. DOI:10.1016/S0020-7373(86)80040-2

2. Salmeron J.L., Mansouri T., Moghadam M.R.S., Mardani A. Learning Fuzzy Cognitive Maps with modified asexual reproduction optimisation algorithm // Knowledge-Based Systems. 2019. Vol. 163. PP. 723-735. DOI:10.1016/j.knosys.2018.09.034

3. Konar A., Chakraborty U.K. Reasoning and unsupervised learning in a fuzzy cognitive map // Information Sciences. 2005. Vol. 170. Iss. 2-4. PP. 419-441. DOI:10.1016/j.ins.2004.03.012

4. Hebb D.O. The Organization of Behavior: A Neuropsychological Theory. London: Psychology Press, 2005. 335 p.

5. Kumbasar T., Eksin İ., Güzelkaya M., Yeşil E. Big Bang Big Crunch Optimization Method Based Fuzzy Model Inversion // Proceedings of the 7th Mexican International Conference on Artificial Intelligence on Advances in Artificial Intelligence (MICAI 2008, Atizapán de Zaragoza, Mexico, 27-31 October 2008). Lecture Notes in Computer Science. Vol. 5317. Berlin, Heidelberg: Springer, 2008. PP. 732-740. DOI:10.1007/978-3-540-88636-5_69

6. Vascak J. Approaches in adaptation of fuzzy cognitive maps for navigation purposes // Proceedings of the 8th International Symposium on Applied Machine Intelligence and Informatics (SAMI, Herlany, Slovakia, 28-30 January 2010). IEEE, 2010. PP. 31-36. DOI:10.1109/SAMI.2010.5423716

7. Papageorgiou E., Stylios C., Groumpos P. Fuzzy Cognitive Map Learning Based on Nonlinear Hebbian Rule // Proceedings of the 16th Australian Conference on Advances in Artificial Intelligence (AI, Perth, Australia, 3-5 December 2003). Lecture Notes in Computer Science. Vol. 2903. Berlin: Springer, Heidelberg, 2003. PP. 256-268. DOI:10.1007/978-3-540-24581-0_22

8. Leu G., Abbass H. A multi-disciplinary review of knowledge acquisition methods: From human to autonomous eliciting agents // Knowledge-Based Systems. 2016. Vol. 105. PP. 1-22. DOI:10.1016/j.knosys.2016.02.012

9. Tselykh A.N., Vasilev V., Tselykh L., Barkovskii S.A. Method Maximizing the Spread of Influence in Directed Signed Weighted Graphs // Advances in Electrical and Electronic Engineering. 2017. Vol. 15. Iss. 2. DOI:10.15598/aeee.v15i2.1950

10. Bertsekas D.P. Constrained Optimization and Lagrange Multiplier Methods. Belmont: Athena Scientific, 1996. PP. 158-297.

11. Tikhonov A., Arsenin V. Solutions of Ill-Posed Problems. New York: Wiley, 1977. 272 p.

12. Banini G.A., Bearman R.A. Application of fuzzy cognitive maps to factors affecting slurry rheology // International Journal of Mineral Processing. 1998. Vol. 52. Iss. 4. PP. 233-244. DOI:10.1016/S0301-7516(97)00071-9

13. Bertsekas D.P. The Method of Multipliers for Equality Constrained Problems // Constrained Optimization and Lagrange Multiplier Methods. New York: Elsevier, 1982. PP. 95-157.

14. Tselykh A., Vasilev V., Tselykh L. Ferreira F.A.F. Influence control method on directed weighted signed graphs with deterministic causality // Annals of Operations Research. 2020. DOI:10.1007/s10479-020-03587-8

15. Tselykh A., Vasilev V., Tselykh L. Assessment of influence productivity in cognitive models // Artificial Intelligence Review. 2020. DOI:10.1007/s10462-020-09823-8


Review

For citations:


Vasiliev V..., Tselykh A..., Tselykh L... Method for Validating Graph Models Based on the Effective Control Algorithm. Proceedings of Telecommunication Universities. 2020;6(3):58-65. (In Russ.) https://doi.org/10.31854/1813-324X-2020-6-3-58-65

Views: 2601


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


ISSN 1813-324X (Print)
ISSN 2712-8830 (Online)