A study and performance evaluation of computer network under the environment of bipolar complex fuzzy partition Heronian mean operators

Abstract

The goal of this paper is to study and assessment of the performance of a computer network with the assistance of partition Heronian mean (PHM) operators in the environment of bipolar complex fuzzy (BCF) information. In today's world computers play a significant role in both professional and personal lives. With the advancement of technology, networking arrived in the space and we continuously advanced from wired network innovation to wireless network innovation. A computer network is a gathering of two or more computer systems that are associated together to share information and resources. It can be considered the base of communication in the area of information technology. Thus, for studying and performance evaluation of a computer network, firstly, this paper contains BCF partition Heronian mean (BCFPHM), BCF weighted partition Heronian mean (BCFWPHM), BCF partition geometric Heronian mean (BCFPGHM), and BCF weighted partition geometric Heronian mean (BCFWPGHM) and their corresponding properties. After that, this paper contains a decision-making (DM) mechanism constructed on the explored operators and a genuine-life example to evaluate the performance of a computer network based on the DM mechanism in the environment of BCF information. The last part of the paper contains the comparison of the explored mechanism of DM and operators with certain current work for exhibiting the capacity and profits of the explored work.