Complex Multi-Fuzzy Relation for Decision Making using Uncertain Periodic Data

  • Authors

    • Yousef Al-Qudah Universiti Kebangsaan Malaysia
    • Nasruddin Hassan Universiti Kebangsaan Malaysia
    2018-09-20
    https://doi.org/10.14419/ijet.v7i4.16976
  • Complex Multi-Fuzzy Set, Complex Multi-Fuzzy Relation, Multi-Fuzzy Set, Complex Fuzzy Set, Decision Making.
  • Abstract

    We introduce a new type of relations called complex multi-fuzzy relation (CMFR). The novelty of CMFR lies in the ability of complex multi- membership functions to achieve more range of values while handling uncertainty of data that is periodic in nature. The application of complex multi-fuzzy sets is then discussed in determining: the influence of modern methods of education on student performance, and the time required for the former to affect the latter. A comparison between different existing relations and CMFR to show the ascendancy of our proposed CMFR is provided. Thereafter, a few related concepts such as complement, union, intersection and inverse along with several propositions are discussed, followed by the composition of CMFR along with some related theorems. Finally, the notions of symmetric, transitive, reflexive, and equivalence complex multi-fuzzy relations are established in our work.

  • References

    1. [1] L. A. Zadeh, “Fuzzy set,†Information and Computation, vol. 8, no. 3, pp. 338–353, 1965.

      [2] K. Alhazaymeh and N. Hassan, “Vague soft multiset theory,†International Journal of Pure and Applied Mathematics, vol. 93, no. 4, pp. 511-523, 2014.

      [3] K. Alhazaymeh, and N. Hassan, “Generalized interval-valued vague soft set,†Applied Mathematical Sciences, vol. 7, no. 140, pp. 6983-6988, 2013.

      [4] K. Alhazaymeh and N. Hassan, “Vague soft set relations and functions,†Journal of Intelligent and Fuzzy Systems, vol.28, no. 3, pp. 1205-1212, 2015.

      [5] Y. Al-Qudah and N. Hassan, “Bipolar fuzzy soft expert set and its application in decision making,†International Journal of Applied Decision Sciences, vol. 10, no. 2, pp.175-191, 2017.

      [6] A. Indahingwati, M.B.N. Wajdi, D.E. Susilo, N. Kurniasih, R. Rahim, “Comparison analysis of TOPSIS and fuzzy logic methods on fertilizer selection,†International Journal of Engineering and Technology, vol. 7, no. 2.3, pp.109-114, 2018.

      [7] D. Shyafary, H. Rony, R. Malani, W.A.Sartika, “Image mosaicking by using random seeds generation based on fuzzy membership function,†International Journal of Engineering and Technology, vol. 7, no. 2.2, pp. 70-74, 2018.

      [8] T. Pathinathan, S. Santhoshkumar, “Type-2 pentagonal fuzzy numbers and its application to get equivalent proverbs in two different languages,†International Journal of Engineering and Technology, vol. 7, no. 2.33, pp. 926-933, 2018.

      [9] Ar. Pandipriya, J. Vimala, S. Sabeena Begam, “Lattice ordered interval-valued hesitant fuzzy soft sets in decision making problem,†International Journal of Engineering and Technology, vol. 7, no. 1.3, pp. 52-55, 2018.

      [10] S. Sebastian and T. V. Ramakrishnan, “Multi-fuzzy sets,†International Mathematical Forum, vol. 5, no. 50, pp. 2471-2476, 2010.

      [11] S. Sebastian and T. V. Ramakrishnan, “Multi-fuzzy sets: An extension of fuzzy sets,†Fuzzy Information and Engineering, vol. 3, no. 1, pp. 35-43, 2011.

      [12] J. A. Goguen, “L-fuzzy sets,†J Math. Anal. Appl, vol. 18, no. 1, pp.145-174, 1967.

      [13] K. T. Atanassov, “Intuitionistic fuzzy sets,†Fuzzy Sets and Systems, vol. 20, no. 1, pp. 87-96, 1986.

      [14] D. Ramot, R. Milo, M. Friedman, and A. Kandel, “Complex fuzzy sets,†IEEE Transactions on Fuzzy Systems, vol. 10, no. 2, pp. 171-186, 2002.

      [15] D. Ramot, M. Friedman, G. Langholz, and A. Kandel, “Complex fuzzy logic,†IEEE Transactions on Fuzzy Systems, vol. 11, no. 4, pp. 450-461, 2003.

      [16] A. Alkouri and A. Salleh, “Complex intuitionistic fuzzy sets,†in International Conference on Fundamental and Applied Sciences, AIP Conference Proceedings, vol. 1482, pp. 464-470, 2012.

      [17] Y. Al-Qudah and N. Hassan, “Operations on complex multi-fuzzy sets,†Journal of Intelligent and Fuzzy Systems, vol. 33, no. 3, pp. 1527-1540, 2017.

      [18] L. A. Zadeh, “Similarity relations and fuzzy orderings,†Information Sciences, vol. 3, no. 2, pp. 177-200, 1971.

      [19] S. Dutta and M.K. Chakraborty, “Fuzzy relation and fuzzy function over fuzzy sets: a retrospective,†Soft Computing, vol. 19, no. 1, pp. 99-112, 2015.

      [20] A. Kheniche, B. Baets, and L. Zedam, “Compatibility of fuzzy relations,†International Journal of Intelligent Systems, vol. 31, no. 3, pp. 240-256, 2016.

      [21] C. Kocak, “A new high order fuzzy ARMA time series forecasting method by using neural networks to define fuzzy relations,†Mathematical Problems in Engineering, vol. 2015, Article ID 128097, 2015.

      [22] G. Zhang, T. S. Dillon, K.-Y. Cai, J. Ma, and J. Lu, “Operation properties and δ-equalities of complex fuzzy sets,†International Journal of Approximate Reasoning, vol. 50, no. 8, pp. 1227-1249, 2009.

      [23] G. Zhang, T. S. Dillon, K. Y. Cai, J. Ma, and J. Lu, “δ-equalities of complex fuzzy relations,†In Proceedings of the IEEE International 24th Conference on Advanced Information Networking and Applications, pp. 1218-1224, April 2010.

      [24] P. Burillo and H. Bustince, “Intuitionistic fuzzy relations part I,†Mathware and Soft Computing, vol.2, pp.5-38. 1995.

      [25] H. Bustince and P. Burillo, “Structures on intuitionistic fuzzy relations,†Fuzzy Sets and Systems, vol. 78, no. 3, pp.293-303, 1996.

      [26] A.S. Thomas and S.J. John, “Multi-fuzzy rough sets and relations,†Annals of Fuzzy Mathematics and Informatics, vol. 7, no. 5, pp.807-815, 2014.

      [27] A. Alkouri and A.R Salleh, “Complex Atanassov’s intuitionistic fuzzy relations,†Abstract and Applied Analysis, vol. 2013, Article ID 287382, 2013.

      [28] K. Alhazaymeh and N. Hassan, “Generalized vague soft expert set,†International Journal of Pure and Applied Mathematics, vol. 93, no. 3, pp.351-360, 2014.

      [29] K. Alhazaymeh, and N. Hassan, “Application of generalized vague soft expert set in decision making,†International Journal of Pure and Applied Mathematics, vol. 93, no. 3, pp.361-367, 2014.

      [30] K. Alhazaymeh and N. Hassan, “Mapping on generalized vague soft expert set,†International Journal of Pure and Applied Mathematics, vol. 93, no. 3, pp.369-376, 2014.

      [31] A. Al-Quran and N. Hassan, “Neutrosophic vague soft expert set theory,†Journal of Intelligent and Fuzzy Systems, vol.30, no. 6, pp. 3691-3702, 2016.

      [32] F. Adam and N. Hassan, “Properties on the multi Q-fuzzy soft matrix,†AIP Conference Proceedings, vol. 1614, pp. 834-839, 2014.

      [33] F. Adam and N. Hassan, “Q-fuzzy soft set,†Applied Mathematical Sciences, vol. 8, no. 174, pp. 8689-8695, 2014.

      [34] F. Adam and N. Hassan, “Operations on Q-fuzzy soft set,†Applied Mathematical Sciences, vol. 8, no. 175, pp. 8697-8701, 2014.

      [35] F. Adam and N. Hassan, “Q-fuzzy soft matrix and its application,†AIP Conference Proceedings, vol. 1602, pp. 772-778, 2014.

      [36] N. Hassan and S. Sahrin, “A mathematical model of nutrient management for pineapple cultivation in Malaysia,†Advances in Environmental Biology, vol. 6, no.5, pp. 1868-1872, 2012.

      [37] N. Hassan, L.W. Siew and S.Y. Shen, “Portfolio decision analysis with maximin criterion in the Malaysian stock market,†Applied Mathematical Sciences, vol. 6, no. 110, pp. 5483-5486, 2012.

      [38] N. Hassan and L.L. Loon, “Goal programming with utility function for funding allocation of a university library,†Applied Mathematical Sciences, vol. 6, no. 110, pp. 5487- 5493, 2012.

      [39] N. Hassan and B.A. Halim, “Mathematical modelling approach to the management of recreational tourism activities at Wetland Putrajaya,†Sains Malaysiana, vol. 41, no. 9, pp. 1155- 1161, 2012.

      [40] N. Hassan, S. Safiai, N.H.M. Raduan and Z. Ayop, “Goal programming formulation in nutrient management for chilli plantation in Sungai Buloh, Malaysia,†Advances in Environmental Biology, vol. 6, no. 12, pp. 4008-4012, 2012.

      [41] N. Hassan, M.M. Tabar and P. Shabanzade, “A ranking model of data envelopment analysis as a centralized multi objective resource allocation problem tool,†Australian Journal of Basic and Applied Sciences, vol. 4, no. 10, pp. 5306-5313, 2010.

      [42] N. Hassan, M.M. Tabar and P. Shabanzade, “Resolving multi objectives resource allocation problem based on inputs and outputs using data envelopment analysis method,†Australian Journal of Basic and Applied Sciences, vol. 4, no. 10, pp. 5320-5325, 2010.

      [43] N. Hassan and M.M. Tabar, “The relationship of multiple objectives linear programming and data envelopment analysis,†Australian Journal of Basic and Applied Sciences, vol. 5, no. 11, pp. 1717-1714, 2011.

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  • How to Cite

    Al-Qudah, Y., & Hassan, N. (2018). Complex Multi-Fuzzy Relation for Decision Making using Uncertain Periodic Data. International Journal of Engineering & Technology, 7(4), 2437-2445. https://doi.org/10.14419/ijet.v7i4.16976

    Received date: 2018-08-06

    Accepted date: 2018-08-17

    Published date: 2018-09-20