Examples of WeightedSum

eu.planets_project.pp.plato.model.aggregators.WeightedSum
This {@link Aggregator} class performs weighted addition,i.e. the result value for a node is the result of summing up the values of the child nodes, and multiplying this with the relative weight of the node @author cbu
eu.scape_project.planning.model.aggregators.WeightedSum
This {@link Aggregator} class performs weighted addition,i.e. the result value for a node is the result of summing up the values of the child nodes, and multiplying this with the relative weight of the node @author cbu
org.neuroph.core.input.WeightedSum
Optimized version of weighted input function @author zoran
tv.floe.metronome.classification.neuralnetworks.input.WeightedSum

Examples of eu.planets_project.pp.plato.model.aggregators.WeightedSum

        // (0.4->0.51 and 0.6->0.49)
        // a change by 0.11 is considered a lot, therefor this weighting is stable
        sf1.setWeight(0.43);
        sf2.setWeight(0.57);
        
        ResultNode resultRoot = new ResultNode(root, new WeightedSum(), alternatives);
        resultRoot.analyseSensitivity(weightModifier,
                SensitivityAnalysisTestFactory.getSensitivityTest(root, new WeightedSum(), alternatives));
        
        assert(!resultRoot.isSensitive());
    }

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Examples of eu.scape_project.planning.model.aggregators.WeightedSum

        aggMultResultNodes.add(new ResultNode(plan.getTree().getRoot(), new WeightedMultiplication(), plan
            .getAlternativesDefinition().getConsideredAlternatives()));


        aggSumResultNodes.clear();
        // calculate result nodes for all considered alternatives
        ResultNode sumResultNode = new ResultNode(plan.getTree().getRoot(), new WeightedSum(), plan
            .getAlternativesDefinition().getConsideredAlternatives());
        aggSumResultNodes.add(sumResultNode);


        knockedoutAlternativePresent = acceptableAlternatives.size() != plan.getAlternativesDefinition()
            .getConsideredAlternatives().size();

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Examples of eu.scape_project.planning.model.aggregators.WeightedSum


        // FIXME HK reintroduce SENSITIVITY analysis for large trees - Plato 3.1
        if (plan.getTree().getRoot().getAllLeaves().size() < MAX_SENSITIVITY_ANALYSIS_LEAVES) {
            log.debug("Starting sensitivity analysis ... ");
            rootNode.analyseSensitivity(new SimpleIterativeWeightModifier(), new OrderChangeCountTest(plan.getTree()
                .getRoot(), new WeightedSum(), alternatives));
            log.debug("Sensitivity analysis took: " + (System.currentTimeMillis() - start) + "ms.");
        } else {
            log.debug("Sensitivity analysis NOT CONDUCTED: Too many leaves.");
        }
    }

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Examples of eu.scape_project.planning.model.aggregators.WeightedSum

        showAllConsideredAlternativesForWeightedSum = false;
        weightedSumResultTreeShownAlternatives = acceptableAlternatives;


        aggSumResultNodes.clear();
        // calculate result nodes for all considered alternatives
        ResultNode sumResultNode = new ResultNode(plan.getTree().getRoot(), new WeightedSum(), plan
            .getAlternativesDefinition().getConsideredAlternatives());
        aggSumResultNodes.add(sumResultNode);


        planetsExecutablePlanPrettyFormat = formatExecutablePlan(plan.getExecutablePlanDefinition().getExecutablePlan());

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Examples of eu.scape_project.planning.model.aggregators.WeightedSum


        selectedPlans.clear();
        // We also need the scores of the alternatives - for each selected plan
        for (int pId : planSelection.getSelectedPlans()) {
            Plan plan = planManager.loadPlan(pId);
            ResultNode result = new ResultNode(plan.getTree().getRoot(), new WeightedSum(), plan
                .getAlternativesDefinition().getConsideredAlternatives());
            selectedPlans.add(new PlanInfo(pId, result, plan.getPlanProperties()));
        }
        // Init calculation classes
        this.calculator = new KBrowserCalculator(planLeaves, nrRelevantPlans);

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Examples of org.neuroph.core.input.WeightedSum

public class InputNeuron extends Neuron {
  private static final long serialVersionUID = 1L;




  public InputNeuron() {
            super(new WeightedSum(), new Linear());
        }

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Examples of tv.floe.metronome.classification.neuralnetworks.input.WeightedSum

import tv.floe.metronome.classification.neuralnetworks.activation.Linear;


public class InputNeuron extends Neuron {


    public InputNeuron() {
        super(new WeightedSum(), new Linear());
    }

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Examples of tv.floe.metronome.classification.neuralnetworks.input.WeightedSum


  protected transient double error = 0;
  
  public Neuron() {
    
    this.inputFunction = new WeightedSum();
    this.activationFunction = new Step();
    
    
    this.inConnections = new ArrayList<Connection>();
    this.outConnections = new ArrayList<Connection>();

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Examples of tv.floe.metronome.classification.neuralnetworks.input.WeightedSum

    
    if (0 == layerIndex) {
      n = new InputNeuron();
      
    } else {
      n = new Neuron(new WeightedSum(), new Sigmoid());
    }
    
    
    
    return n;

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