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RBE_DSS

PURPOSE ^

Fuzzy system tuning with RBE-DSS

SYNOPSIS ^

function fis=RBE_DSS(fis,InTrain,OutTrain,params,options,etTuningInfo,axPIDiagram,axOutputDataDiagram)

DESCRIPTION ^

 Fuzzy system tuning with RBE-DSS

 fis=RBE_DSS(fis,InTrain,OutTrain,params,options,etTuningInfo,axPIDiagram,axOutputDataDiagram)

 Fuzzy system tuning using a "hill climbing" approach and
 creation of new rules. It works with MISO systems and trapezoid shaped
 linguistic terms ('trapmf'). Using the method RBE-DSS.
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 Parameters
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 fis - complex structure describing the fuzzy inference system
 InTrain  - N by M matrix containing the input data, where N is number of
            data points and M is the number of input dimensions
 OutTrain - N by 1 matrix containing the output data, where N is number of
            data points and 1 is the number of output dimensions
 params   - parameters of the fuzzy inference
 options  - Options of the system tuning
    options(1)  Number of allowed decimals
    options(2)  Coefficient for the step
    options(3)  SimilarityTreshold
                Indicates the treshold value below which two sets
                are merged in one. The treshold is expressed in
                proportion of the range of the actual input
                variable. Its value is inside the interval [0,1].
    options(4)  Number of iterations
    options(5)  info display during iteration
    options(6)  Save FIS and info after each calculation step
    options(7)  IncrementTreshold
                Increase (double) step if the amelioration of the 
                performance index is greater than
                IncrementTreshold during an iteration. 
    options(8)  DecrementTreshold
                Decrease (halve) step if the amelioration of the 
                performance index is smaller than
                DecrementTreshold during an iteration. 
    options(9)  Merge simlar sets after each iteration
    options(10) Merge similar rules after each iteration
    options(11) Plot Performance Index
    Options(12) Plot original and calculated data
    options(13) Tuning method type
    options(14) Performance index type
    options(15) Stop the iteration when the performance index 
                falls below this value. It is expressed in proportion of
                the range of the output linguistic variable.
    options(16) Core width in proportion of the range
    options(17) Support width in proportion of the range
 etTuningInfo - handle of the editbox displaying the tuning preferences
 axPIDiagram - handles of the axes PI
 axOutputDataDiagram - handles of the OutputDataDiagram
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 Returned values
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 fis - complex structure describing the fuzzy inference system
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 Remarks
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 The centre of the core is is used as reference point.
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 Zsolt Csaba Johanyák, johanyak.csaba@gamf.kefo.hu, v. 3.4,  30 Sep 2007.

CROSS-REFERENCE INFORMATION ^

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