[1. Angelova, V. Investigations in the Ares of Soft Computing. Targeted State of the Art Report. – Cybernetics and Information Technologies, Vol. 9, 2009, No 1, pp. 18-24. http://www.cit.iit.bas.bg/CIT_09/v9-1/18-24.pdf]Search in Google Scholar
[2. Atanassova, V., L. Doukovska, A. Michalíková, I. Radeva. Intercriteria Analysis: From Pairs to Triples. – Notes on Intuitionistic Fuzzy Sets, Vol. 22, 2016, No 5, pp. 98-110.]Search in Google Scholar
[3. Brans, J. P., B. Mareschal. The PROMCALC&GAIA Decision Support System for Multicriteria Decision Aid. – Decision Support Systems, North-Holland, Vol. 12, 1994, pp. 279-310.10.1016/0167-9236(94)90048-5]Search in Google Scholar
[4. Copland, T., T. Koller, J. Murrin. Valuation: Measure and Managing the Value of Companies. New York, John Wiley, 2002.]Search in Google Scholar
[5. Kishor, D. R., N. B. Venkateswarlu. Hybridization of Expectation-Maximization and K-Means Algorithms for Better Clustering Performance. – Cybernetics and Information Technologies, Vol. 16, 2016, No 2, pp. 16-34.10.1515/cait-2016-0017]Open DOISearch in Google Scholar
[6. Ilieva, G. Decision Making Methods in Agent Based Modeling. – In: Proc. of Workshop on Applications of Software Agents, 2011, pp. 8-17.]Search in Google Scholar
[7. Ilieva, G. A Fuzzy Approach for Bidding Strategy Selection. – Cybernetics and Information Technologies, Vol. 12, 2012, No 1, pp. 61-69.10.2478/cait-2012-0005]Open DOISearch in Google Scholar
[8. Ilieva, G. TOPSIS Modification with Interval Type-2 Fuzzy Numbers. – Cybernetics and Information Technologies, Vol. 16, 2016, No 2, pp. 60-68.10.1515/cait-2016-0020]Search in Google Scholar
[9. Ilieva, G. Group Decision Analysis with Interval Type-2 Fuzzy Numbers. – Cybernetics and Information Technologies, Vol. 17, 2017, No 1, pp. 31-44.10.1515/cait-2017-0003]Open DOISearch in Google Scholar
[10. Georgieva, P., I. Popchev. Application of Q-Measure in a Real Time Fuzzy System for Managing Financial Assets. – International Journal of Soft Computing (IJSC), Vol. 3, 2012, No 4, pp. 21-38.10.5121/ijsc.2012.3403]Search in Google Scholar
[11. Georgieva, P., I. Popchev, S. Stoyanov. A Multi-Step Procedure for Asset Allocation in Case of Limited Resources. – Cybernetics and Information Technologies, Vol. 15, 2015, No 3, pp. 41-51.10.1515/cait-2015-0040]Search in Google Scholar
[12. Ghazanfari, M., S. Rouhani, M. Jafari. A Fuzzy TOPSIS Model to Evaluate the Business Intelligence Competencies of Port Community Systems. – Polish Maritime Research, Vol. 2, Vol. 21, 2014, No 82, pp. 86-96.10.2478/pomr-2014-0023]Search in Google Scholar
[13. Herrera-Viedma, E., Herrera, F. Chiclana, M. Luque. Some Issues on Consistency of Fuzzy Preference Relations. – European Journal of Operational Research, 2004, pp. 98-109.10.1016/S0377-2217(02)00725-7]Open DOISearch in Google Scholar
[14. Mavrov, D., I. Radeva, K. Atanassov, L. Doukovska, I. Kalaykov. Inter Criteria Software Design: Graphic Interpretation within the Intuitionistic Fuzzy Triangle. – In: Proc. of International Symposium on Business Modeling and Software Design (BMSD’15), Milan, Italy, SCITEPRESS – Science and Technology Publications, 2015, pp. 279-283.]Search in Google Scholar
[15. Popchev, I., V. Peneva. An Algorithm for Comparison of Fuzzy Sets. – Fuzzy Sets and Systems, Norht-Holland, Amsterdam, Vol. 60, 1993, No 1, pp. 59-65.10.1016/0165-0114(93)90289-T]Search in Google Scholar
[16. Peneva, V., I. Popchev. Fuzzy Ordering on the Base of Multicriteria Aggregation. – Cybernetics and Systems, Vol. 29, 1998, No 6, pp. 613-623.10.1080/019697298125542]Search in Google Scholar
[17. Peneva, V., I. Popchev. Fuzzy Logic Operators in Decision-Making. – International Journal Cybernetics and Systems, Vol. 30, 1999, No 8, pp. 725-745.10.1080/019697299124966]Search in Google Scholar
[18. Peneva, V., I. Popchev. Aggregation on Fuzzy Numbers in a Decision Making Situation. – Cybernetics and Systems, Vol. 32, 2001, Issue 8, pp. 871-885.10.1080/019697201753229845]Search in Google Scholar
[19. Peneva, V., I. Popchev. Aggregation of Fuzzy Relations Using Weighting Function. – Compt. Rend. Acad. bulg. Sci., Vol. 60, 2007, No 10, pp. 1047-1052.]Search in Google Scholar
[20. Peneva, V., I. Popchev. Fuzzy Criteria Importance with Weighting Functions. – Comp. Rend. Acad. bulg. Sci. Vol. 61, 2008, No 3, pp. 293-300.]Search in Google Scholar
[21. Peneva, V., I. Popchev. Models for Fuzzy Multicriteria Decision Making Based on Fuzzy Relations. – Compt. Rend. Acad. bulg. Sci., Vol. 62, 2009, No 5, pp. 551-558.]Search in Google Scholar
[22. Peneva, I., I. Popchev. Fuzzy Multi-Criteria Decision Making Algorithms. – Comp. Rend. Acad. bulg. Sci., Vol. 63, 2010, No 7, pp. 979-991.]Search in Google Scholar
[23. Popchev, I., I. Radeva. MAP-Cluster: An Approach for Latent Cluster Identification. – In: Proc. of Synergy of Computational Economics and Financial and Industrial Systems IFAC CEFIS’2007, 2007, Istanbul, pp. 63-67.]Search in Google Scholar
[24. Porter, M. On Competition, Clusters and Competition: New Agendas for Companies, Governments, and Institutions. Boston, Harvard Business School Press, 1998.]Search in Google Scholar
[25. Radeva, I. An Approach to Strategic Integration in Economic Clustering. – In: International Conference Automatics and Informatics’10, Sofia, 2010, pp. II-385-388.]Search in Google Scholar
[26. Radeva, I. Strategic Integration with MAP – CLUSTER Software System. – Cybernetics and Information Technologies, Vol. 10, 2010, No 2, pp. 78-93.]Search in Google Scholar
[27. Rouhani, S., M. Ghazanfari, M. Jafari. Evaluation Model of Business Intelligence for Enterprise Systems Using Fuzzy TOPSIS. – Expert Systems with Applications, Vol. 39, 2012, pp. 3764-3771.10.1016/j.eswa.2011.09.074]Search in Google Scholar
[28. Szmidt, E., J. Kacprzyk, K. Atanassov. Intuitionistic Fuzzy Modifications of Some Peneva-Popchev Formulas for Estimation of Preference Degree. Pary 1. – In: Issue in IFSs and GNs, Vol. 10, 2013, pp. 12-20.]Search in Google Scholar
[29. InterCriteria Research Portal. http://www.intercriteria.net/publications]Search in Google Scholar