참고문헌 (24)

1. American Pet Production Association. Pet Industry Market Size & Ownership Statistics [Internet], Available: https://www.americanpetproducts.org/press_industrytrends.asp. 

2. M. Martini, M. Fenati, M. Agosti, R. Cassini, M. Drigo, N. Ferro, C. Guglielmini, I. Masiero, M. Signorini, and R. Busetto, "A surveillance system for diseases of companion animals in the Veneto region (Italy)," Scientific and Technical Review of the Office International des Epizooties, vol. 36, no. 3, pp. 1007-1014, 2017. DOI: 10.20506/rst.36.3.2732. 

   상세보기

3. J. H. Choi, E. J. Park, and H. J. Lee, "A study on the market trends analysis of companion animal food and products in Korea," Journal of Korea Contents Association, vol. 19, no. 8, pp. 115-122, 2019. DOI: 10.5392/JKCA.2019.19.08.115. 

   원문보기 상세보기

4. Korea Companion Animal Report 2021, Kukmin Bank Business Research Institute [Internet], Available: https://www.kbfg.com/kbresearch/report/reportView.do?reportId2000160. 

5. K. B. Kim, D. H. Song, and Y. W. Woo, "Machine intelligence can guide pet dog health pre-diagnosis for casual owner: a neural network approach," International Journal of Bio-Science and Bio-Technology, vol. 6, no. 2, pp. 83-90, 2014. DOI: 10.14257/ijbsbt.2014.6.2.08. 

   상세보기

6. K. B. Kim, D. H. Song, and H. J. Park, "CareMyDog: Pet dog disease information system with PFCM inference for pre-diagnosis by caregiver," Journal of Information and Communication Convergence Engineering, vol. 19, no. 1, pp. 29-35, 2021. DOI: 10.6109/jicce.2021.19.1.29. 

   원문보기 상세보기

7. L. Marlinda, W. Widiyawati, W. Indrarti, and R. Widiastuti, "Dog disease expert system using certainty factor method," SinkrOn : Jurnal dan Penelitian Teknik Informatika, vol. 4, no. 2, pp. 98-104, 2020. DOI: 10.33395/sinkron.v4i2.10538. 

   

8. M. Y. Munirah, S. Suriawati, and P. P. Teresa, "Design and development of online dog diseases diagnosing system," International Journal of Information and Education Technology, vol. 6, no. 11, pp. 913-916, 2016. DOI: 10.7763/ijiet.2016.v6.816. 

   

9. K. B. Kim, D. H. Song, and Y. W. Woo, "Ad-hoc pet dog healthcare diagnosing system using machine intelligence," in Proceedings of International Workshop (Bioscience and Medical Research), vol. 33, pp. 11-13, 2013. DOI: 10.14257/astl.2013.33.03. 

10. K. B. Kim and D. H. Song, "Intelligent automatic extraction of canine cataract object with dynamic controlled fuzzy C-means based quantization," International Journal of Electrical & Computer Engineering, vol. 8, no. 2, pp. 666-672, 2018. DOI: 10.11591/ijece.v8i2.pp666-672. 

    상세보기

11. Y. Namkoong, G. Heo, and Y. W. Woo, "An extension of possibilistic fuzzy c-means with regularization," in International Conference on Fuzzy Systems, IEEE, pp. 1-6, 2010. DOI: 10.1109/fuzzy.2010.5584538. 

12. Y. Kanzawa and S. Miyamoto, "Regularized fuzzy c-means clustering and its behavior at point of infinity," Journal of Advanced Computational Intelligence and Intelligent Informatics, vol. 23, no. 3, pp. 485-492, 2019. DOI: 10.20965/jaciii.2019.p0485. 

    상세보기

13. K. B. Kim, H. J. Park, and D. H. Song, "Intelligent home disease pre-diagnosis system for Korean traditional medicine using neural networks," International Journal of Information and Communication Technology, vol. 8, no. 1, pp. 1-9, 2016. DOI: 10.1504/ijict.2016.073634. 

    

14. Kosko B. Neural networks and fuzzy systems: A dynamical systems approach to machine intelligence, Prentice Hall. 1992. 

15. T. D. Bui, T. H. Nong, and T. K. Dang, "Improving learning rule for fuzzy associative memory with combination of content and association," Neurocomputing, vol. 149, pp. 59-64, 2015. DOI: 10.1016/j.neucom.2014.01.063. 

    상세보기

16. M. Vajgl and I. Perfiljeva, "Autoassociative fuzzy implicative memory on the platform of fuzzy preorder," in 16th World Congress of the International Fuzzy Systems Association (IFSA) and the 9th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT): Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology, vol. 30, pp. 1598-1603 2015. DOI: 10.2991/ifsaeusflat-15.2015.228. 

17. M. E. Valle and A. C. de Souza, "On the recall capability of recurrent exponential fuzzy associative memories based on similarity measures," Mathware & Soft Computing Magazine, vol. 22, no. 1, pp. 33-39, 2015. 

18. J. H. Lee and D. H. Song, "A Fast Scalable Image Restoration based on Fuzzy Associative Memory Structure," International Information Institute (Tokyo). Information; Koganei, vol. 20, no. 1B, pp. 543-548, 2017. 

19. K. Kim and D. Song, "Colored facial image restoration by similarity enhanced implicative fuzzy association memory," Indonesian Journal of Electrical Engineering and Computer Science, vol. 13, no. 1, pp. 199-204, 2019. DOI: 10.11591/ijeecs.v13.i1.pp199-204. 

    상세보기

20. M. Aldape-Perez, C. Yanez-Marquez, O. Camacho-Nieto, and A. J. Arguelles-Cruz, "An associative memory approach to medical decision support systems," Computer Methods and Programs in Biomedicine, vol. 106, no. 3, pp. 287-307, 2012. 

    상세보기

21. I. Perova and Y. Bodyanskiy, "Fast medical diagnostics using auto-associative neuro-fuzzy memory," International Journal of Computing, vol. 16, no. 1, pp. 34-40, 2017. DOI: 10.47839/ijc.16.1.869. 

    

22. M. Aldape-Perez, A. Alarcon-Paredes, C. Yanez-Marquez, I. Lopez-Yanez, and O. Camacho-Nieto, "An associative memory approach to healthcare monitoring and decision making," Sensors, vol. 18, no. 8, pp. 2690, 2018. DOI: 10.3390/s18082690. 

    상세보기

23. L. Li, W. Pedrycz, T. Qu, and Z. Li, "Fuzzy associative memories with autoencoding mechanisms," Knowledge-Based Systems, vol. 191, pp. 105090, 2020. DOI: 10.1016/j.knosys.2019.105090. 

    상세보기

24. P. Sussner and M. E. Valle, "Fuzzy associative memories and their relationship to mathematical morphology," Handbook of Granular Computing, Ch. 33, pp. 733-754, 2008. DOI: 10.1002/9780470724163.ch33.