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Many computing methods have been studied in an intuitionistic fuzzy environment to enhance the resourcefulness of intuitionistic fuzzy sets in modelling real-life problems, among which correlation coefficient is prominent. This paper proposes a new intuitionistic fuzzy correlation algorithm via intuitionistic fuzzy deviation, variance, and covariance by taking into account the complete parameters of intuitionistic fuzzy sets. This new computing technique not only evaluates the strength of relationship between the intuitionistic fuzzy sets but also indicates whether the intuitionistic fuzzy sets have either positive or negative linear relationships. The proposed technique is substantiated with some theoretical results and numerically validated to be superior in terms of performance index in contrast to some hitherto methods. Multi-criteria decision-making processes involving pattern recognition and students’ admission process are determined with the aid of the proposed intuitionistic fuzzy correlation algorithm coded with JAVA programming language.

A Novel Intuitionistic Fuzzy Correlation Algorithm and Its Applications in Pattern Recognition and Student Admission Process