fuzzy-logic-toolkit
A mostly MATLAB-compatible fuzzy logic toolkit for Octave.
Select category:
Evaluation
Plotting
File Input/Output of Fuzzy Inference Systems
Command-Line Creation and Modification of Fuzzy Inference Systems
Text Representation of Fuzzy Inference Systems
Membership Functions
T-Norms and S-Norms (in addition to max/min)
Complete Fuzzy Inference System Demos
Fuzzy Clustering Functions
For a given domain, set of fuzzy function values, and defuzzification method, return the defuzzified (crisp) value of the fuzzy function.
Return the crisp output(s) of an FIS for each row in a matrix of crisp input values.
For a given domain, set of parameters, membership function type, and optional hedge and not_flag, return the corresponding y-values for the membership function.
Generate and plot a surface (or 2-dimensional curve) showing one FIS output as a function of two (or one) of the FIS inputs.
Plot the membership functions defined for the specified FIS input or output variable on a single set of axes.
Read the information in an FIS file, and using this information, create and return an FIS structure.
Save the specified FIS currently in the Octave workspace to a file named by the user.
Add a membership function to an existing FIS structure and return the updated FIS.
Add a list of rules to an existing FIS structure and return the updated FIS.
Add an input or output variable to an existing FIS structure and return the updated FIS.
Create and return a new FIS structure using the argument values provided.
Remove a membership function from an existing FIS structure and return the updated FIS.
Remove an input or output variable from an existing FIS structure and return the updated FIS.
Set a property (field) value of an FIS structure and return the updated FIS.
Return or print the property (field) values of an FIS structure specified by the arguments.
Print all of the property (field) values of the FIS structure and its substructures.
Show the rules for an FIS structure in verbose, symbolic, or indexed format.
For a given domain X and parameters PARAMS (or [A1 C1 A2 C2]), return the corresponding Y values for the difference between two sigmoidal membership functions.
For a given domain X and parameters PARAMS (or [SIG1 C1 SIG2 C2]), return the corresponding Y values for the two-sided Gaussian composite membership function.
For a given domain X and parameters PARAMS (or [SIG C]), return the corresponding Y values for the Gaussian membership function.
For a given domain X and parameters PARAMS (or [A B C]), return the corresponding Y values for the generalized bell-shaped membership function.
For a given domain X and parameters PARAMS (or [A B C D]), return the corresponding Y values for the pi-shaped membership function.
For a given domain X and parameters PARAMS (or [A1 C1 A2 C2]), return the corresponding Y values for the product of two sigmoidal membership functions.
For a given domain X and parameters PARAMS (or [A C]), return the corresponding Y values for the sigmoidal membership function.
For a given domain X and parameters PARAMS (or [A B]), return the corresponding Y values for the S-shaped membership function.
For a given domain X and parameters PARAMS (or [A B C D]), return the corresponding Y values for the trapezoidal membership function.
For a given domain X and parameters PARAMS (or [A B C]), return the corresponding Y values for the triangular membership function.
For a given domain X and parameters PARAMS (or [A B]), return the corresponding Y values for the Z-shaped membership function.
Return the algebraic product of the input.
Return the algebraic sum of the input.
Return the bounded difference of the input.
Return the bounded sum of the input.
Return the drastic product of the input.
Return the drastic sum of the input.
Return the Einstein product of the input.
Return the Einstein sum of the input.
Return the Hamacher product of the input.
Return the Hamacher sum of the input.
Demonstrate the use of the Octave Fuzzy Logic Toolkit to approximate a non-linear function using a Sugeno-type FIS with linear output functions.
Demonstrate the use of newfis, addvar, addmf, addrule, and evalfis to build and evaluate an FIS.
Demonstrate the use of the Octave Fuzzy Logic Toolkit to read and evaluate a Sugeno-type FIS stored in a file.
Demonstrate the use of the Octave Fuzzy Logic Toolkit to read and evaluate a Mamdani-type FIS stored in a file.
Demonstrate the use of linear output membership functions to simulate constant membership functions.
Demonstrate the use of the Octave Fuzzy Logic Toolkit to read and evaluate a Mamdani-type FIS stored in a file.
Demonstrate the use of the Octave Fuzzy Logic Toolkit to read and evaluate a Sugeno-type FIS with multiple outputs stored in a text file.
Using the Fuzzy C-Means algorithm, calculate and return the soft partition of a set of unlabeled data points.
Using the Gustafson-Kessel algorithm, calculate and return the soft partition of a set of unlabeled data points.
Return the partition coefficient for a given soft partition.
Return the partition entropy for a given soft partition.
Return the Xie-Beni validity index for a given soft partition.
Package: fuzzy-logic-toolkit