Examples of NEATLink

Examples of org.encog.neural.neat.NEATLink

117
118
119
120
121
122
123
124
125
  }
 
  private void link(
      double weight, NEATNeuron from, NEATNeuron to, boolean recurrent)
  {
    NEATLink l = new NEATLink(weight, from, to, recurrent);
    from.getOutputboundLinks().add(l);
    to.getInboundLinks().add(l);
  }
View Full Code Here

Examples of org.encog.neural.neat.NEATLink

573
574
575
576
577
578
579
580
581
582
583
        if( element==-1 ) {
          System.out.println("test");
        }
        final NEATNeuron toNeuron = neurons.get(element);

        final NEATLink link = new NEATLink(linkGene.getWeight(),
            fromNeuron, toNeuron, linkGene.isRecurrent());

        fromNeuron.getOutputboundLinks().add(link);
        toNeuron.getInboundLinks().add(link);
View Full Code Here

Examples of org.encog.neural.neat.NEATLink

52
53
54
55
56
57
58
59
60
61
62
63
   
    for(int i=0;i<activationFunctions.length;i++) {
      activationFunctions[i] = new ActivationSteepenedSigmoid();
    }
   
    links.add( new NEATLink(0,2,1.0));
    links.add( new NEATLink(1,2,2.0));
   
    NEATNetwork result = new NEATNetwork(1,1,links,activationFunctions);
       
    return result;
  }
View Full Code Here

Examples of org.encog.neural.neat.NEATLink

94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
      double weight = output.getData(0);
      if (Math.abs(weight) > this.minWeight) {
        weight = (Math.abs(weight) - this.minWeight) * c
            * Math.signum(weight);
        linkList.add(new NEATLink(source.getId(), target.getId(),
            weight));
      }
    }

    // now create biased links
    input.clear();
    final int d = substrate.getDimensions();
    final List<SubstrateNode> biasedNodes = substrate.getBiasedNodes();
    for (final SubstrateNode target : biasedNodes) {
      for (int i = 0; i < d; i++) {
        input.setData(d + i, target.getLocation()[i]);
      }

      final MLData output = cppn.compute(input);

      double biasWeight = output.getData(1);
      if (Math.abs(biasWeight) > this.minWeight) {
        biasWeight = (Math.abs(biasWeight) - this.minWeight) * c
            * Math.signum(biasWeight);
        linkList.add(new NEATLink(0, target.getId(), biasWeight));
      }
    }

    // check for invalid neural network
    if (linkList.size() == 0) {
View Full Code Here
TOP
Copyright © 2018 www.massapi.com. All rights reserved.
All source code are property of their respective owners. Java is a trademark of Sun Microsystems, Inc and owned by ORACLE Inc. Contact coftware#gmail.com.