Bipolar fuzzy attribute implications

Agrawal R, Srikant R (1993) Fast algorithms for mining association rules. In: Proc. 20th int. conf. very large data bases. VLDB 1215:487–499

Agrawal R, Imieliński T, Swami A (1993) Mining association rules between sets of items in large databases. In: Proceedings of the 1993 ACM SIGMOD international conference on management of data, pp. 207-216

Akram M, Amjad U, Davvaz B (2021) Decision-making analysis based on bipolar fuzzy N-soft information. Comp. Appl. Math. 40:182

Ali G, Akram M, Koam ANA, Alcantud JCR (2019) Parameter reductions of bipolar fuzzy soft sets with their decision-making algorithms. Symmetry 11(8):949

Ali G, Akram M, Alcantud JCR (2020) Attributes reductions of bipolar fuzzy relation decision systems. Neural computing and applications 32(14):10051–10071

Belohlavek R, Vychodil V (2005a) Fuzzy attribute logic: attribute implications, their validity, entailment, and non-redundant basis. In : Liu et al. (ed.): Proceedings of eleventh international fuzzy systems association world congress, pp. 622-627

Belohlavek R, Vychodil V (2005b) Fuzzy attribute implications: computing non-redundant bases using maximal independent sets. In: Proceedings of Australian conference on artificial intelligence, pp. 1126-1129

Belohlavek R, Vychodil V (2006) Attribute implications in a fuzzy setting. In: Proceedings of ICFCA, pp. 45-60

Bloch I (2011) Lattices of fuzzy sets and bipolar fuzzy sets, and mathematical morphology. Information Sciences 181(10):2002–2015

Carpineto C, Romano G (2004) Concept data analysis: theory and application. John Willey and Sons Ltd.

Ganter B (1999) Attribute exploration with background knowledge. Theoretical computer science 217(2):215–233

Glodeanu CV(2012) Attribute exploration in a fuzzy setting. In: Proceedings of ICFCA 2012, pp. 114-129

Kumar CHA (2012) Fuzzy clustering based formal concept analysis for association rules mining. Applied artificial intelligence 26(3):274–301

Kumar CA, Srinivas S (2010) Mining associations in health care data using formal concept analysis and singular value decomposition. Journal of biological system 18(4):787–807

Riaz M, Therim ST (2021) A robust extension of VIKOR method for bipolar fuzzy sets using connection numbers of SPA theory based metric spaces. Artificial intelligence review 54:561–591

She QK, Zhai YH (2008) Generating complete set of implications for formal contexts. Knowledge-based systems 21:429–433

Singh PK (2019) Bipolar fuzzy concept learning using Next Neighbor and Euclidean distance. Soft Computing 23(12):4503–4520

Singh PK (2019a) Multi–granulation based graphical analytics of three–way bipolar neutrosophic contexts. Cognitive Computations 11(4):513–528

Singh PK (2019b) Three-way bipolar neutrosophic concept lattice. In: Irem otay et al. Fuzzy multi-criteria decision making using neutrosophic sets, Studies in fuzziness and soft computing 369:417–432

Singh PK (2020) Bipolar δ-equal complex fuzzy concept lattice with its application. Neural computing and applications 32(7):2405–2422

Singh PK (2021) Bipolarity in multi–way fuzzy context and its analysis using m–way granulation. Granular computing. https://doi.org/10.1007/s41066-021-00277-z

Singh PK, Kumar CHA (2014a) A note on bipolar fuzzy graph representation of concept lattice. International journal of computing science and mathematics 5(4):381–393

Singh PK, Kumar CHA (2014b) Bipolar fuzzy graph representation of concept lattice. Information Sciences 288:437–448

Singh PK, Aswani Kumar CH (2017) Attribute implications in data with fuzzy attributes using Armstrong axioms. In: Proceedings of international conference on energy, communication, data analytics and soft computing (ICECDS) 2017, pp. 637-641

Wei G, Alsaadi FE, Hayat T, Alsaedi A (2018) Bipolar fuzzy hamacher aggregation operators in multiple attribute decision making. Int. J. Fuzzy Syst. 20:1–12

Welch H (1957) Taoism: the parting of the way. Boston: Beach Press 1957

Wille R (1982) Restructuring lattice theory: an approach based on hierarchies of concepts. In: I. Rival (eds.): Ordered Sets, Reidel Dordrect-Boston, pp. 445-470

Zhang WR (1994) Bipolar fuzzy sets and relations: a computational framework for cognitive modeling and multiagent decision analysis. In: Proc IEEE Conf 1994, pp.305–309.

Zhang WR (2018) From equilibrium--based business intelligence to information conservational quantum--fuzzy cryptography- a cellular transformation of bipolar fuzzy sets to quantum intelligence machinery, IEEE transactions on fuzzy systems 26(2) (2018) 656- 669.