66 lines
1.8 KiB
HTML
66 lines
1.8 KiB
HTML
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<center><h3> Optimization example </h3></center>
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Java code to optimize fuzzy sets' parameters and fuzzy rule's weights<p>
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<table border=0 bgcolor=#ccfccc><tr><td>
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<pre>
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//---
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// Load FIS (Fuzzy Inference System)
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//---
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FIS fis = FIS.load("fcl/qualify.fcl");
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RuleBlock ruleBlock = fis.getFunctionBlock().getRuleBlock();
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//---
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// Create a list of parameter to optimize
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//---
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ArrayList<Parameter> parameterList = new ArrayList<Parameter>();
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// Add variables.
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// Note: Fuzzy sets' parameters for these
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// variables will be optimized
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Parameter.parameterListAddVariable(parameterList
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, fis.getVariable("scoring"));
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Parameter.parameterListAddVariable(parameterList
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, fis.getVariable("credLimMul"));
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// Add every rule's weight
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for( Rule rule = ruleBlock )
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Parameter.parameterListAddRule(parameterList, rule);
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//---
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// Create an error function to be
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// optimzed (i.e. minimized)
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//---
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ErrorFunctionQualify errorFunction = new ErrorFunctionQualify();
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//---
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// Optimize (using 'Delta jump optimization')
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//---
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OptimizationDeltaJump optimizationDeltaJump =
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new OptimizationDeltaJump(ruleBlock
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, errorFunction, parameterList);
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// Number optimization of iterations
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optimizationDeltaJump.setMaxIterations(20);
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optimizationDeltaJump.optimize(true);
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</pre>
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</td></tr></table>
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<p>
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The error funcion (in this particular case, ErrorFunctionQualify) can be just any error function, the structure for the code should be like this:
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<table border=0 bgcolor=#ccfccc><tr><td>
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<pre>
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public class ErrorFunctionQualify extends ErrorFunction {
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public double evaluate(RuleBlock ruleBlock) {
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double error;
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// Caculate your desired error here...
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return error;
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}
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}
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</pre>
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</td></tr></table>
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