In this note, we show by counterexamples that some results of Qiu and colleagues [On the restudy of fuzzy complex analysis: Part I. The sequence and series of fuzzy complex numbers and their convergences, Fuzzy Sets and Systems 115 (2000) 445–450; On the restudy of fuzzy complex analysis: Part II. The continuity and differentiation of fuzzy complex functions, Fuzzy Sets and Systems 120 (2001) 5...

The objective of this paper is to finds the lower and upper bounds Nordhaus-Gaddum inequalities fuzzy chromatic number for anti-fuzzy graph. This analyzes index complementary anti graphs in some cases. A theorem proved graph be k-critical. Examples are provided derive vertex coloring these graphs.

Since the product of complex numbers and rectangular fuzzy (RFCN) is not necessarily a RFCN in former linear system (FCLS), scalar multiplication addition operations (FCN) based on new representation FCN are proposed. We also introduce method for solving FCLS, which can convert FCLS into two distinct systems. One an n×n system, other (mn)×(mn) real where n number unknown variables, m substituti...

The objective of this paper is to investigate the applications of complex fuzzy sets. The novelty of the complex fuzzy set lies in the range of values its membership function may attain. In contrast to a traditional fuzzy membership function, this range is not limited to [0, 1], but extended to the unit circle in the complex plane. Thus, the complex fuzzy set provides a mathematical framework f...

Abstract This paper presents a new complex system systemic. Here, we are working in a fuzzy environment, so we have to adapt all the previous concepts and results that were obtained in a non-fuzzy environment, for this fuzzy case. The direct and indirect influences between variables will provide the basis for obtaining fuzzy and/or non-fuzzy relationships, so that the concepts of coverage and i...

in this paper, a new approach of modeling for artificial neural networks (ann) models based on the concepts of ann and fuzzy regression is proposed. for this purpose, we reformulated ann model as a fuzzy nonlinear regression model while it has advantages of both fuzzy regression and ann models. hence, it can be applied to uncertain, ambiguous, or complex environments due to its flexibility. in ...