99 lines
4.2 KiB
HTML
99 lines
4.2 KiB
HTML
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<center><h3> Java Classes </h3></center>
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How this package works and how classes are organized is briefly explained here.<p>
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<ul>
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<li> A fuzzy inference system (<i><b>FIS</b></i>) is composed by one or more <i><b>FuncionBlock</b></i> class, like in FCL. E.g.:
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<table border=0 bgcolor=#ccfccc><tr><td> <pre>
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FUNCTION_BLOCK functionBlock1
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...
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END_FUNCTION_BLOCK
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FUNCTION_BLOCK functionBlock2
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...
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END_FUNCTION_BLOCK
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</pre> </td></tr></table><p>
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<li> Each <i><b>FuncionBlock</b></i> is composed by one or more <i><b>RuleBlock</b></i> class and some <i><b>Variables</b></i>, as well as <i><b>Fuzzyfiers</b></i> and <i><b>Defuzzifiers</b></i>. Again, like in FCL, e.g.:
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<table border=0 bgcolor=#ccfccc><tr><td> <pre>
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FUNCTION_BLOCK functionBlockName
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VAR_INPUT
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...
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END_VAR
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VAR_OUTPUT
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...
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END_VAR
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FUZZIFY inputVariable
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...
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END_FUZZIFY
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DEFUZZIFY outputVariable
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...
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END_DEFUZZIFY
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RULEBLOCK No1
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...
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END_RULEBLOCK
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END_FUNCTION_BLOCK
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</pre> </td></tr></table><p>
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<li> Each <i><b>Rule</b></i> class is composed by an antecedent (<b>IF</b> part) and a consequent (<b>THEN</b> part), e.g.:<br>
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<table border=0 bgcolor=#ccfccc><tr><td> RULE 1 : IF service IS poor OR food IS rancid THEN tip IS cheap;<br> </td></tr></table>
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<ul>
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<li> Antecedent: <i>"service IS poor OR food IS rancid"</i>
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<li> Consequent: <i>"tip IS cheap"</i>. Note that there may be more than one consequent.
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<li> A rule implication (or activation) method can be defined (althought FCL does not allow different implication method for each rule, it can be defined at RULEBLOCK level).
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e.g.: <table border=0 bgcolor=#ccfccc><tr><td> ACT : MIN; // Use 'min' activation method </td></tr></table>
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</ul>
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<p>
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<li> Consequents are a 'collection' of <i><b>RuleTerms</b></i> classes (e.g. <i>"tip IS cheap"</i> is a RuleTerm)
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<p>
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<li> An Antecedent is represented by a <i><b>RuleExpression</b></i> class. A <i><b>RuleExpression</b></i> is just two terms connected by one <i><b>RuleConnectionMethod</b></i> (rule conectors are 'AND', 'OR' and 'NOT')<br>
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e.g.: <table border=0 bgcolor=#ccfccc><tr><td> service IS poor OR food IS rancid <br> </td></tr></table>
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<ul>
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<li> First term: <i>"service IS poor"</i>
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<li> Second term: <i>"food IS rancid"</i>
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<li> RuleConnectionMethod is <i>'OR'</i>
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</ul>
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<b>Note:</b> Each term can be either a <i><b>RuleTerm</b></i> or a <i><b>RuleExpression</b></i>, this definition is recursive, so arbitrarly complex expressions can be created.
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<p>
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<li> Each <i><b>RuleTerm</b></i> is defined by a <i><b>Variable</b></i> and a <i><b>LinguisticTermName</b></i>.
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e.g.: <table border=0 bgcolor=#ccfccc><tr><td> service IS poor </td></tr></table>
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<ul>
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<li> <i><b>Variable</b></i>: service
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<li> <i><b>LinguisticTermName</b></i>: 'poor'
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<li> Connector: 'IS'
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</ul>
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It can also be 'negated' e.g.: <table border=0 bgcolor=#ccfccc><tr><td> service IS NOT excellent<br> </td></tr></table>
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<p>
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<li> Each <i><b>Variable</b></i> has a <i><b>name</b></i> and some <i><b>LinguisticTerms</b></i>
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e.g.: For an input variable: <table border=0 bgcolor=#ccfccc><tr><td><pre>
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FUZZIFY service // Fuzzify input variable 'service': {'poor', 'good' , 'excellent'}
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TERM poor := (0, 1) (4, 0) ;
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TERM good := (1, 0) (4,1) (6,1) (9,0);
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TERM excellent := (6, 0) (9, 1);
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END_FUZZIFY
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</pre></td></tr></table><p>
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e.g.: For an output variable: <table border=0 bgcolor=#ccfccc><tr><td><pre>
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DEFUZZIFY tip // Defzzzify output variable 'tip' : {'cheap', 'average', 'generous' }
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TERM cheap := (0,0) (5,1) (10,0);
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TERM average := (10,0) (15,1) (20,0);
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TERM generous := (20,0) (25,1) (30,0);
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METHOD : COG; // Use 'Center Of Gravity' defuzzification method
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DEFAULT := 0; // Default value is 0 (if no rule activates defuzzifier)
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END_DEFUZZIFY
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</pre></td></tr></table>
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As you can see, for an output variable you need to specify an accumulation (or <i><b>RuleAgrregationMethod</b></i>) and a <i><b>Defuzzifier</b></i>.
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e.g.: <table border=0 bgcolor=#ccfccc><tr><td><pre>
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ACCU : MAX; // Use 'max' accumulation method
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METHOD : COG; // Use 'Center Of Gravity' defuzzification method
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</pre></td></tr></table>
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</ul>
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</td></tr></table>
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