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JOONE(Java Object-Oriented Network Engine)使用初探

Posted on 2007-09-30 16:03 tanzek 閱讀(5989) 評論(2) 編輯收藏所屬分類: 技術學習

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/*
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?*?JOONE?-?Java?Object?Oriented?Neural?Engine
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?*? http://joone.sourceforge.net
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?*
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?*?XOR_using_NeuralNet.java
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?*
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? */
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package ?study;
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import ?org.joone.engine. * ;
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import ?org.joone.engine.learning. * ;
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import ?org.joone.io. * ;
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import ?org.joone.net. * ;
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import ?java.util.Vector;
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public ? class ?XOR_using_NeuralNet? implements ?NeuralNetListener? {
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???? private ?NeuralNet????????????nnet? = ? null ;
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???? private ?MemoryInputSynapse??inputSynapse,?desiredOutputSynapse;
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???? private ?MemoryOutputSynapse?outputSynapse;
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????LinearLayer????input;
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????SigmoidLayer?hidden,?output;
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???? boolean ?singleThreadMode? = ? true ;
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????
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???? // ?XOR?input
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???? private ? double [][]????????????inputArray? = ? new ? double [][]? {
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???????? { 0.0 ,? 0.0 } ,
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???????? { 0.0 ,? 1.0 } ,
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???????? { 1.0 ,? 0.0 } ,
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???????? { 1.0 ,? 1.0 }
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????} ;
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????
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???? // ?XOR?desired?output
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???? private ? double [][]????????????desiredOutputArray? = ? new ? double [][]? {
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???????? { 0.0 } ,
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???????? { 1.0 } ,
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???????? { 1.0 } ,
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???????? { 0.0 }
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????} ;
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????
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???? /**
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?????*? @param ?args?the?command?line?arguments
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????? */
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???? public ? static ? void ?main(String?args[])? {
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????????XOR_using_NeuralNet?xor? = ? new ?XOR_using_NeuralNet();
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????????
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????????xor.initNeuralNet();
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????????xor.train();
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????????xor.interrogate();
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????}
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????
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???? /**
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?????*?Method?declaration
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????? */
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???? public ? void ?train()? {
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????????
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???????? // ?set?the?inputs
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????????inputSynapse.setInputArray(inputArray);
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????????inputSynapse.setAdvancedColumnSelector( " 1,2 " );
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???????? // ?set?the?desired?outputs
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????????desiredOutputSynapse.setInputArray(desiredOutputArray);
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????????desiredOutputSynapse.setAdvancedColumnSelector( " 1 " );
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????????
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???????? // ?get?the?monitor?object?to?train?or?feed?forward
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????????Monitor?monitor? = ?nnet.getMonitor();
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????????
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???????? // ?set?the?monitor?parameters
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????????monitor.setLearningRate( 0.8 );
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????????monitor.setMomentum( 0.3 );
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????????monitor.setTrainingPatterns(inputArray.length);
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????????monitor.setTotCicles( 5000 );
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????????monitor.setLearning( true );
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????????
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???????? long ?initms? = ?System.currentTimeMillis();
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???????? // ?Run?the?network?in?single-thread,?synchronized?mode
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????????nnet.getMonitor().setSingleThreadMode(singleThreadMode);
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????????nnet.go( true );
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????????System.out.println( " Total?time=? " + (System.currentTimeMillis()? - ?initms) + " ?ms " );
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????}
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????
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???? private ? void ?interrogate()? {
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???????? // ?set?the?inputs
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????????inputSynapse.setInputArray(inputArray);
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????????inputSynapse.setAdvancedColumnSelector( " 1,2 " );
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????????Monitor?monitor = nnet.getMonitor();
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????????monitor.setTrainingPatterns( 4 );
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????????monitor.setTotCicles( 1 );
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????????monitor.setLearning( false );
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????????MemoryOutputSynapse?memOut? = ? new ?MemoryOutputSynapse();
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???????? // ?set?the?output?synapse?to?write?the?output?of?the?net
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????????
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???????? if (nnet != null )? {
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????????????nnet.addOutputSynapse(memOut);
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????????????System.out.println(nnet.check());
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????????????nnet.getMonitor().setSingleThreadMode(singleThreadMode);
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????????????nnet.go();
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????????????
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???????????? for ( int ?i = 0 ;?i < 4 ;?i ++ )? {
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???????????????? double []?pattern? = ?memOut.getNextPattern();
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????????????????System.out.println( " Output?pattern?# " ? + ?(i + 1 )? + ? " = " ? + ?pattern[ 0 ]);
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????????????}
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????????????System.out.println( " Interrogating?Finished " );
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????????}
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????}
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????
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???? /**
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?????*?Method?declaration
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????? */
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???? protected ? void ?initNeuralNet()? {
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????????
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???????? // ?First?create?the?three?layers
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????????input? = ? new ?LinearLayer();
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????????hidden? = ? new ?SigmoidLayer();
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????????output? = ? new ?SigmoidLayer();
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????????
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???????? // ?set?the?dimensions?of?the?layers
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????????input.setRows( 2 );
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????????hidden.setRows( 3 );
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????????output.setRows( 1 );
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????????
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????????input.setLayerName( " L.input " );
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????????hidden.setLayerName( " L.hidden " );
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????????output.setLayerName( " L.output " );
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????????
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???????? // ?Now?create?the?two?Synapses
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????????FullSynapse?synapse_IH? = ? new ?FullSynapse();???? /* ?input?->?hidden?conn.? */
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????????FullSynapse?synapse_HO? = ? new ?FullSynapse();???? /* ?hidden?->?output?conn.? */
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????????
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???????? // ?Connect?the?input?layer?whit?the?hidden?layer
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????????input.addOutputSynapse(synapse_IH);
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????????hidden.addInputSynapse(synapse_IH);
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????????
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???????? // ?Connect?the?hidden?layer?whit?the?output?layer
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????????hidden.addOutputSynapse(synapse_HO);
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????????output.addInputSynapse(synapse_HO);
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????????
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???????? // ?the?input?to?the?neural?net
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????????inputSynapse? = ? new ?MemoryInputSynapse();
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????????
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????????input.addInputSynapse(inputSynapse);
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????????
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???????? // ?The?Trainer?and?its?desired?output
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????????desiredOutputSynapse? = ? new ?MemoryInputSynapse();
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????????
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????????TeachingSynapse?trainer? = ? new ?TeachingSynapse();
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????????
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????????trainer.setDesired(desiredOutputSynapse);
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????????
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???????? // ?Now?we?add?this?structure?to?a?NeuralNet?object
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????????nnet? = ? new ?NeuralNet();
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????????
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????????nnet.addLayer(input,?NeuralNet.INPUT_LAYER);
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????????nnet.addLayer(hidden,?NeuralNet.HIDDEN_LAYER);
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????????nnet.addLayer(output,?NeuralNet.OUTPUT_LAYER);
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????????nnet.setTeacher(trainer);
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????????output.addOutputSynapse(trainer);
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????????nnet.addNeuralNetListener( this );
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????}
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????
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???? public ? void ?cicleTerminated(NeuralNetEvent?e)? {
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????}
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????
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???? public ? void ?errorChanged(NeuralNetEvent?e)? {
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????????Monitor?mon? = ?(Monitor)e.getSource();
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???????? if ?(mon.getCurrentCicle()? % ? 100 ? == ? 0 )
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????????????System.out.println( " Epoch:? " + (mon.getTotCicles() - mon.getCurrentCicle()) + " ?RMSE: " + mon.getGlobalError());
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????}
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????
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???? public ? void ?netStarted(NeuralNetEvent?e)? {
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????????Monitor?mon? = ?(Monitor)e.getSource();
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????????System.out.print( " Network?started?for? " );
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???????? if ?(mon.isLearning())
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????????????System.out.println( " training. " );
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???????? else
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????????????System.out.println( " interrogation. " );
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????}
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????
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???? public ? void ?netStopped(NeuralNetEvent?e)? {
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????????Monitor?mon? = ?(Monitor)e.getSource();
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????????System.out.println( " Network?stopped.?Last?RMSE= " + mon.getGlobalError());
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????}
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????
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???? public ? void ?netStoppedError(NeuralNetEvent?e,?String?error)? {
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????????System.out.println( " Network?stopped?due?the?following?error:? " + error);
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????}
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????
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}
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# re: JOONE(Java Object-Oriented Network Engine)使用初探回復 更多評論

2007-12-02 15:39 by longmiaost

我最近也在研究這個東東，有沒有詳細的說明，或者學習資料！！可否發給我一份longmiaost@126.com

# re: JOONE(Java Object-Oriented Network Engine)使用初探 回復 更多評論

2008-06-23 02:51 by xia fei

你這過簡單例子，可以說幫了很多人，我早前看過軟件開發的文章，有一個方法叫plagarism programming, 你這例子，反映了PP原來是很實在。。。。Good Job......

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