Java source code)

1. Package com. sweetop. test;
3. Import java. Io. serializable;
4. Import java. util. arrays;
5. Import java. util. vector;
7. Import org. joone. Engine. fullsynapse;
8. Import org. joone. Engine. linearlayer;
9. Import org. joone. Engine. Monitor;
10. Import org. joone. Engine. neuralnetevent;
11. Import org. joone. Engine. neuralnetlistener;
12. Import org. joone. Engine. pattern;
13. Import org. joone. Engine. sigmoidlayer;
14. Import org. joone. Engine. Learning. teachingsynapse;
15. Import org. joone. Io. fileinputsynapse;
16. Import org. joone. Io. fileoutputsynapse;
17. Import org. joone. Io. memoryinputsynapse;
18. Import org. joone. Io. memoryoutputsynapse;
19. Import org.joone.net. Neuralnet;
21. Public class test implements neuralnetlistener, serializable {
22. /**
23. *
24. */
25. Private Static final long serialversionuid = 61750666816215273l;
26. Private Neuralnet nNet = NULL;
27. Private memoryinputsynapse inputsynapse, desiredoutputsynapse;
28. Private memoryoutputsynapse outputsynapse;
30. // XOR Input
31. Private double [] [] inputarray = new double [] [] {1.0, 1.0 },
32. {1.0, 2.0 },{ 2.0, 2.0 },{ 2.0, 3.0 },{ 1.0, 3.0 }};
34. // XOR desired output
35. Private double [] [] desiredoutputarray = new double [] [] {{ 2.0/10 },
36. {3.0/10}, {4.0/10}, {5.0/10}, {4.0/10 }};
38. Protected void initneuralnet (){
39. // First create the Three Layers
40. Linearlayer input = new linearlayer ();
41. Sigmoidlayer hidden = new sigmoidlayer ();
42. Sigmoidlayer output = new sigmoidlayer ();
44. Input. setlayername ("input ");
45. Hidden. setlayername ("hidden ");
46. Output. setlayername ("output ");
48. // Set the dimensions of the layers
49. Input. setrows (2 );
50. Hidden. setrows (3 );
51. Output. setrows (1 );
53. // Now create the two synapses
54. Fullsynapse synapse_ih = new fullsynapse ();/* input-> hidden conn .*/
55. Fullsynapse synapse_ho = new fullsynapse ();/* hidden-> Output Conn .*/
57. // Connect the input layer whit the hidden layer
58. Input. addoutputsynapse (synapse_ih );
59. Hidden. addinputsynapse (synapse_ih );
61. // Connect the hidden layer whit the output layer
62. Hidden. addoutputsynapse (synapse_ho );
63. Output. addinputsynapse (synapse_ho );
65. // The input to the neural net
66. Inputsynapse = new memoryinputsynapse ();
67. Input. addinputsynapse (inputsynapse );
69. // The output of the neural net
70. Outputsynapse = new memoryoutputsynapse ();
72. Output. addoutputsynapse (outputsynapse );
74. // The trainer and its desired output
75. Desiredoutputsynapse = new memoryinputsynapse ();
77. Teachingsynapse trainer = new teachingsynapse ();
79. Trainer. setdesired (desiredoutputsynapse );
80. NNet = new Neuralnet ();
82. NNet. addlayer (input, Neuralnet. input_layer );
83. NNet. addlayer (hidden, Neuralnet. hidden_layer );
84. NNet. addlayer (output, Neuralnet. output_layer );
85. NNet. setteacher (trainer );
86. Output. addoutputsynapse (trainer );
87. Train ();
88. // File
89. }
91. Public void test (double [] [] d ){
92. Inputsynapse. setinputarray (d );
93. Inputsynapse. setadvancedcolumnselector ("1, 2 ");
94. NNet. getmonitor (). settotcicles (1 );
95. NNet. Start ();
96. NNet. getmonitor (). Go ();
97. For (Object O: outputsynapse. getallpatterns ()){
98. Pattern P = (pattern) O;
99. System. Out. println (10 * P. getarray () [0]);
100. }
101. }
102. Public void train (){
103. // Set the inputs
104. Inputsynapse. setinputarray (inputarray );
105. Inputsynapse. setadvancedcolumnselector ("1, 2 ");
106. // Set the desired outputs
107. Desiredoutputsynapse. setinputarray (desiredoutputarray );
108. Desiredoutputsynapse. setadvancedcolumnselector ("1 ");
110. // Get the monitor object to train or feed forward
111. Monitor = nNet. getmonitor ();
113. // Set the monitor parameters
114. Monitor. setlearningrate (0.8 );
115. Monitor. setmomentum (0.3 );
116. Monitor. settrainingpatterns (inputarray. Length );
117. Monitor. settotcicles (100000 );
118. Monitor. setlearning (true );
119. NNet. addneuralnetlistener (this );
120. NNet. Start ();
121. NNet. getmonitor (). Go ();
122. For (Object O: outputsynapse. getallpatterns ()){
123. Pattern P = (pattern) O;
124. System. Out. println (10 * P. getarray () [0]);
125. }
126. }
128. Public void cicleterminated (neuralnetevent e ){
130. }
132. Public void errorchanged (neuralnetevent e ){
134. }
136. Public void netstarted (neuralnetevent e ){
137. // Todo auto-generated method stub
139. }
141. Public void netstopped (neuralnetevent e ){
142. // Todo auto-generated method stub
144. }
146. Public void netstoppederror (neuralnetevent E, string error ){
148. }
150. }