Published Paper Details:

A hybrid intelligent system is a set of artificial intelligence (AI) tools which can be used to handle difficult medical challenges in healthcare. Materials informatics can be advantageous for industrial engineering and manufacturing applications when analyzed from a data mining approach. Knowledge Discovery in Databases (KDD) is the goal of the data mining process. KDD uses processes such as data selection, data mining, data preprocessing, pattern assessment, and data transformation to extract knowledge from raw datasets. To extract knowledge from massive datasets, many data mining approaches like association, clustering, and classification are utilized. This work reviewed the literature on KDD applications in the wide area of manufacturing by a particular focus on the types of data functions to be performed. Description, characterization and association, classification, prediction, clustering, and evolution analysis are the primary data mining functions to be done. In addition, the Knowledge Discovery using Hybrid Data Mining Approach module's settings and outcomes are assessed.