| 1 | // This file is a part of Framsticks SDK. http://www.framsticks.com/ |
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| 2 | // Copyright (C) 1999-2015 Maciej Komosinski and Szymon Ulatowski. |
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| 3 | // See LICENSE.txt for details. |
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| 4 | |
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| 5 | #ifndef _NEUROIMPLFUZZY_H_ |
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| 6 | #define _NEUROIMPLFUZZY_H_ |
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| 7 | |
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| 8 | #include <stdlib.h> |
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| 9 | #include <math.h> |
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| 10 | |
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| 11 | #include <frams/neuro/neuroimpl.h> |
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| 12 | #include <frams/util/sstring.h> |
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| 13 | |
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| 14 | extern ParamEntry NI_FuzzyNeuro_tab[]; |
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| 15 | |
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| 16 | /** Does the fuzzyfication process (of inputs) and defuzzyfication proces (of outpurs) - represents fuzzy rules |
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| 17 | */ |
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| 18 | class NI_FuzzyNeuro : public NeuroImpl |
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| 19 | { |
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| 20 | private: |
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| 21 | |
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| 22 | double *fuzzySets; /// list of four digits which represents fuzzy sets: [0]-l, [1]-m, [2]-n, [3]-r, ... fuzzySet[4*i] = left, fuzzySet[4*i + 1] = midleft, fuzzySet[4*i + 2] = midright, fuzzySet[4*i + 3] = right |
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| 23 | |
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| 24 | /** Determines, which fuzzy set is connected with each input of neuron. For instance third rule: |
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| 25 | * 'IF input3 = fuzzy set #3 AND input5 = fuzzy set #1 then output2 = fuzzy set #6 AND output7 = fuzzy set #5' |
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| 26 | * the variables shoul have values as shown below: |
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| 27 | * RulesDef[4]=2; RulesDef[5]=2; //rule 3: 2 inputs, 2 outputs |
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| 28 | * Rules[2][0]=3, Rules[2][1]=3, Rules[2][2]=5, Rules[2][3]=1, Rules[2][4]=2, Rules[2][5]=6, Rules[2][6]=7, Rules[2][3]=5 |
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| 29 | */ |
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| 30 | int *rulesDef; ///list of rules definitions: nr of inputs in rule 1, nr of outputs in rule 1, ... and so on for each rule |
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| 31 | int **rules; ///list of rules body: input nr, fuzzy set nr, ... , output nr, fuzzy set nr, ... and so on for each rule |
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| 32 | |
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| 33 | /** |
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| 34 | * Sets defuzzyfication parameters: determines - for each rule - cut level <0;1> (minimum membership function of current rule). |
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| 35 | * In fact, defuzzParam remembers the values from 'first layer' - fuzzyfication layer (see neuron at documentation) |
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| 36 | * i.e. rule 1: defuzzParam[0] = 0.3522 |
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| 37 | */ |
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| 38 | double *defuzzParam; /// i.e.: defuzParam[5] = 0.455 means that rule #6 has got a minimum membership function (of given inputs set for this rule) at value 0.455 (it's cut level) |
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| 39 | |
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| 40 | protected: |
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| 41 | |
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| 42 | ///Fuzzy functions |
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| 43 | double TrapeziumFuzz(int which_fuzzy_set, double input_val); |
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| 44 | int Fuzzyfication(); |
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| 45 | int Defuzzyfication(); |
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| 46 | int GetFuzzySetParam(int set_nr, double &left, double &midleft, double &midright, double &right); |
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| 47 | |
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| 48 | public: |
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| 49 | |
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| 50 | int fuzzySetsNr; /// number of fuzzy sets |
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| 51 | int rulesNr; ///number of rules |
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| 52 | SString fuzzySetString; /// strings containing all fuzzy sets given in f0 |
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| 53 | SString fuzzyRulesString; /// strings containing all fuzzy rules given in f0 |
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| 54 | |
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| 55 | NI_FuzzyNeuro() { paramentries = NI_FuzzyNeuro_tab; fuzzySets = defuzzParam = NULL; rulesDef = NULL; rules = NULL; } |
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| 56 | ~NI_FuzzyNeuro(); |
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| 57 | NeuroImpl* makeNew() { return new NI_FuzzyNeuro(); }; |
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| 58 | void go(); |
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| 59 | int lateinit(); |
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| 60 | /** Function build model based on given genotype and conts number of neurons connected with fuzzy neuro, |
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| 61 | also checks number of fuzzy neuron inputs. |
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| 62 | \param genotype genotype to be scanned |
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| 63 | \param inputs number of fuzzy neuron inputs |
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| 64 | \param output number of fuzzy neuron outputs (= number of neurons connected to fuzzy neuron) |
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| 65 | @return success or failure |
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| 66 | **/ |
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| 67 | static int countOuts(const Model *m, const Neuro *fuzzy); |
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| 68 | |
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| 69 | }; |
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| 70 | |
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| 71 | #endif |
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