Jaydev Mishra

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The traditional relational database model may be extended into a fuzzy database model based on the mathematical framework of fuzzy set theory to process imprecise or uncertain information. While designing such a fuzzy relational database model that does not suffer from data redundancy and anomalies, the present authors have defined several fuzzy normal(More)
In the present paper, we have attempted to process indeterminate data through imprecise queries from a database using neutrosophic set which is based on truth, indeterminacy and false membership values. Firstly, we have introduced a similarity measure formula to measure closeness of two neutrosophic data which in turn is used to get the similarity value for(More)
Here, we have focused to process inconsistent data through imprecise queries from a database which consists of neutrosophic and vague set. Neutrosophic set is based on truth, indeterminacy and false membership values where as vague set is based on truth and false membership value. Firstly, we have applied two different similarity measure formulas to measure(More)
Here we proposed a new approach which is based on Neutrosophic logic to help the patient by taking proper decision through pathological report based analysis. Neutrosophic set is used for uncertain data. Fuzzy data is used to handle incomplete data by only truth value and vague data is applicable for uncertain data by truth and false values. But both are(More)
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