Paper Info
Title
Using Artificial Neural Network to Define Fuzzy Comparators in FSQL with the Criterion of some Decision-Maker
Abstract
At present we have a FSQL server available for Oracle漏 Databases, programmed in PL/SQL. This server allows us to query a Fuzzy or Classical Database with the FSQL language (Fuzzy SQL). The FSQL language is an extension of the SQL language which permits us to write flexible (or fuzzy) conditions in our queries to a fuzzy or traditional database. In this paper we have incorporated a method of ranking fuzzy numbers using Neural Networks to compare fuzzy quantities in FSQL. The main advantage is that any user can to train his own fuzzy comparator for any specific problem We consider that this model satisfies the requirements of Data Mining systems (high-level language, efficiency, certainty, interactivity, etc) and this new level of personal configuration makes the system very useful and flexible.
Year
DOI
Venue
2001
10.1007/3-540-45723-2_71
IWANN (2)
Keywords
Field
DocType
satisfiability,artificial neural network,high level language,data mining,decision maker,fuzzy number,neural network
SQL,Data mining,Neuro-fuzzy,Fuzzy classification,Fuzzy set operations,Computer science,Fuzzy logic,Artificial intelligence,Fuzzy Control Language,Fuzzy control system,Fuzzy number
Conference
ISBN
Citations 
PageRank 
3-540-42237-4
5
0.52
References 
Authors
8
3
Name
Order
Citations
PageRank
Ramón Alberto Carrasco17810.67
J. Galindo2547.20
María Amparo Vila Miranda3118293.57