Performance comparison of fuzzy queries on fuzzy database and classical database

Hoque, A H M Sajedul; Ali, Mabruka; Aktaruzzaman, Md.; Mondol, S.K.; Islam, Badar ul

doi:10.1109/icece.2008.4769291

“…In [41] a test database was used to compare the performance of traditional and fuzzy database. The fuzzy schema design for the account of a banking database system was considered which contains information of account number, branch name and balance.…”

Section: Related Work Of Implementing Fuzzy Concept and Schema Design Of Traditional Database Systemmentioning

confidence: 99%

Fuzzy database for medical diagnosis

Parvin¹

2023

Preprint

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A challenge of working with traditional database systems with large amounts of data is that decision making requires numerous comparisons. Health-related database systems are examples of such databases, which contain millions of data entries and require fast data processing to examine related information to make complex decisions. In this thesis, a fuzzy database system is developed by integration of fuzzy inference system (FIS) and fuzzy schema design, and implementing it by SQL in three different health-care contexts; the assessments of heart disease, diabetes mellitus, and liver disorders. The fuzzy database system is implemented with the potential of having any form of data and tested with different types of data value, including crisp, linguistic, and null (i.e., missing) data. The developed system can explore crisp and linguistic data with loosely defined boundary conditions for decision-making. FIS and neural network-based solutions are implemented in MATLAB for the mentioned contexts for the comparison and validation with the dataset used in published works.

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“…In [41] a test database was used to compare the performance of traditional and fuzzy database. The fuzzy schema design for the account of a banking database system was considered which contains information of account number, branch name and balance.…”

Section: Related Work Of Implementing Fuzzy Concept and Schema Design Of Traditional Database Systemmentioning

confidence: 99%

Fuzzy database for medical diagnosis

Parvin¹

2023

Preprint

0

View full text Add to dashboard Cite

A challenge of working with traditional database systems with large amounts of data is that decision making requires numerous comparisons. Health-related database systems are examples of such databases, which contain millions of data entries and require fast data processing to examine related information to make complex decisions. In this thesis, a fuzzy database system is developed by integration of fuzzy inference system (FIS) and fuzzy schema design, and implementing it by SQL in three different health-care contexts; the assessments of heart disease, diabetes mellitus, and liver disorders. The fuzzy database system is implemented with the potential of having any form of data and tested with different types of data value, including crisp, linguistic, and null (i.e., missing) data. The developed system can explore crisp and linguistic data with loosely defined boundary conditions for decision-making. FIS and neural network-based solutions are implemented in MATLAB for the mentioned contexts for the comparison and validation with the dataset used in published works.

show abstract