A novel model to handle uncertainity using Rough sets and Neutrosophic relational maps

Rough set theory is a new mathematical approach for uncertain knowledge. The main advantage of using rough sets is that it does not need any additional or prior information about data. This paper discusses about the hybrid model of rough sets with relational maps to represent the mapping between consistent set of attributes of the dataset to decision classes. The proposed model is tested on 7 led dataset where the rough sets are implemented to get the important reducts of the attributes for decision making and relational maps are used to map reducts with the decision classes. The two extensions of relational maps: Fuzzy relational maps and Neutrosophic relational maps are implemented in the dataset and is shown how Neutrosophic relational maps gives better results as compared to Fuzzy relational maps by considering indeterminate relations.