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In this paper, the authors propose the concept of expert complex fuzzy soft sets as an extension to the classical complex fuzzy set model. Instead of being concerned with the study of the basic set theoretic operations for this model, which are essentially generalizations of the corresponding operations of the complex fuzzy set model, we extend the study of this model through the establishment of the mappings on classes of expert complex fuzzy soft sets. Through these mappings, we introduce the image and inverse image of an expert complex fuzzy soft set, which have immense applications in real-life applications. In addition to presenting the properties of the images and inverse images of this model, we present two numerical examples to demonstrate the utility of these concepts.

Complex fuzzy sets and its accompanying theory although at its infancy, has proven to be superior to classical type-1 fuzzy sets, due its ability in representing time-periodic problem parameters and capturing the seasonality of the fuzziness that exists in the elements of a set. These are important characteristics that are pervasive in most real world problems. However, there are two major problems that are inherent in complex fuzzy sets: it lacks a sufficient parameterization tool and it does not have a mechanism to validate the values assigned to the membership functions of the elements in a set. To overcome these problems, we propose the notion of complex fuzzy soft expert sets which is a hybrid model of complex fuzzy sets and soft expert sets. This model incorporates the advantages of complex fuzzy sets and soft sets, besides having the added advantage of allowing the users to know the opinion of all the experts in a single model without the need for any additional cumbersome operations. As such, this...