Estimation of missing values in fuzzy matrices (FM) and interval-valued fuzzy matrices (IVFM) (original) (raw)

Life Cycle Reliability and Safety Engineering

Abstract

In real life problems, uncertainty also occurs due to loss of information which ultimately results in incomplete information. There are many other reasons which also cause incompleteness, e.g. erroneous data measure, insufficient data collection, lack of evidence, etc. To overcome these situations there are two approaches available, first one we can ignore the object of missing information and second one we predict the unavailable data by estimating the missing values. In the present paper, the concepts of fuzzy matrix and interval valued fuzzy matrix are defined with examples. A new algorithm is proposed to estimate the missing values in fuzzy matrix and its application is illustrated with an example. To generalize the theory of estimation of missing data, another algorithm for interval valued fuzzy matrix is introduced and applied in a numerical problem. In the end discussion and comparison are also given with concluding remarks.

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