sciFLT is a Fuzzy Logic Toolbox for scilab.
TODO:
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* in the next release all function names will be renamed to flt_, e.g.
flt_plotvar
CHANGELOG:
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2014-02-03 Holger Nahrstaedt
* Launch Revision 0.4.5
* savefls bugs corrected (thanks to Chin Luh Tan)
2013-08-22 0.4.4
* xcos palette works under windows
* toolbox loads under windows
2013-08-19 0.4.3
* improved build process
* works with scilab 5.4.1
* addrule added
* fls editor sciFLTEditor added
2011-12-14 0.4.2
* replace wsum by wtsum and waver by wtaver
* help files are generated from the sci files and improved
* definition of all mf functions are defined as in matlab
* a lot of bug fixes in evalfls and in other functions
* xcos support improved
* hedge support
* more demos
2011-11-23 0.4.1
* improved build process
* should work under linux and windows
2011-11-15 Holger Nahrstaedt
* Launch Revision 0.4
* The whole Toolbox is working under scilab 5.3.3
sciFLT have the following properties:
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Types of Fuzzy Logic systems: At this stage, sciFLT can deal with
Takagi-Sugeno Fuzzy and Mamdani fuzzy systems usage.
XCOS support: Member functions, S-Norm, T-Norm, Complement and Fuzzy Logic
System (fls) are supported. Also include a palette.
S-Norm Class supported: Dubois-Prade, Yager, Drastic sum, Einstein, sum,
Algebraic sum, Maximum.
T-Norm Class supported: Dubois-Prade, Yager, Drastic product, Einstein
product, Algebraic product, Minimum
Complement Class supported: One (classic), Yager, Dubois.
Implication method supported: Product, Minimum
Aggregation method supported: Algebraic Sum, Maximum
Defuzzification method supported: Centroide, Bisector, Mean of Maximum,
Largest of Maximum, Smallest of Maximu, Weighted Average, Center Average.
Member functions supported: Triangular, Trapezoidal, Gaussian, Extended
Gaussian, Sigmoidal, Product of two Sigmoidal, Difference of two sigmoidal,
S-Shaped, Z-Shaped, Pi-Shaped. Linear and Const as output for Takagi-Sugeno
type.
GUI editor: Built in editor to change properties, inputs/outputs variables,
member functions, rules.
Fuzzy Clustering
Learning Algorithm