Single-Valued Neutrosophic Partitioned Heronian Mean Operator for Design Intelligence: Evaluating the Quality in Digital Media Art Design Powered by Computational Tools

Abstract

Computational techniques have revolutionized media art and design in the ever
changing digital realm. To assess the caliber of digital media art, this research investigates the 
idea of Design Intelligence, which is the fusion of creativity, computing, and aesthetics. This study 
evaluates digital design projects using a multi-criteria assessment methodology that considers 
important aspects including sustainability, technical execution, creativity, user engagement, and 
utility. As generative algorithms, interactive platforms, and artificial intelligence become more 
prevalent in creative processes, it is imperative that educators and practitioners comprehend the 
qualitative features of these designs. To provide a thorough knowledge of design efficacy in a 
computational setting, the study presents a systematic assessment mechanism backed by expert 
input and qualitative analysis. This study uses the Single-Valued Neutrosophic Partitioned 
Heronian Mean Operator to solve uncertainty problems. The findings provide light on how new 
technologies affect design quality and offer suggestions for raising professional standards and 
educational procedures in the realm of digital media. 

DOI: 10.5281/zenodo.16536120