International Journal of Computing and Mathematics

Granular computation, by various layers of granularity and its implementations in computers, involves a basic human-centered model of decision making.It is directly connected to Artificial Intelligence (AI), which attempts to recognize cognitive functions and its computer applications.In modeling and computation with instability, data granulation has developed as an effective technique, using knowledge granules as the key simulation models used in the granular computation.Artificial intelligence views on granular computation, as such, are still not thoroughly discussed.It discusses the effectiveness of data granulation in artificial intelligence approaches in this article.To such a result, it also explores the basic elements associated with the study of non-geometric patterns, which have rapidly drawn significant interest from researchers.A combination of artificial intelligence findings may enhance granular computing; the theory, technique, and implements of granular computation could aim to resolve a lot of difficulties of machine learning the brain, which has important consequences for the knowledge of artificial intelligence.In conclusion, it expands on the basic, logical problems affecting the data granulation mechanism that propel the search for a valid granular computing framework.