neuralmodel.java

利用Java实现的神经网络工具箱

/*
 * NeuralModel.java	1.0  29/10/2004
 *
 * NeuralNetworkToolkit
 * Copyright (C) 2004 Universidade de Brasília
 *
 * This file is part of NeuralNetworkToolkit.
 *
 * NeuralNetworkToolkit is free software; you can redistribute it and/or modify
 * it under the terms of the GNU General Public License as published by
 * the Free Software Foundation; either version 2 of the License, or
 * (at your option) any later version.
 *
 * NeuralNetworkToolkit is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 * GNU General Public License for more details.
 *
 * You should have received a copy of the GNU General Public License
 * along with NeuralNetworkToolkit; if not, write to the Free Software
 * Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA - 02111-1307 - USA.
 */

package neuralnetworktoolkit;

import java.io.Serializable;
import java.util.Date;

import neuralnetworktoolkit.methods.AboutTrainingMethod;
import neuralnetworktoolkit.neuralnetwork.*;
import neuralnetworktoolkit.normalization.*;

/**
 * A NeuralModel class representes a neural network together with some extra features
 * like used normalization, architecture and statistical results if the network is
 * already trained.
 * 
 * @author <a href="mailto:[e-mail]">Hugo Iver V. Gonçalves</a>
 * @author <a href="mailto:[e-mail]">Rodrigo C. M. Coimbra</a>
 */
public class NeuralModel implements Serializable {
	
	/**
	 * The neural network.
	 */
	private INeuralNetwork neuralNetwork;
	
	/**
	 * Normalization used.
	 */
	private INormalization inputNormalization,
						  outputNormalization;
	/**
	 * Training method information.
	 */
	private AboutTrainingMethod methodInfo;
	
	/**
	 * Statistical results of the training of the neural network.
	 */
	private StatisticalResults statisticalResults;
	
	/**
	 * A Date object to model some time aspects.
	 */
	private Date date;
	
	/**
	 * The network architecture.
	 */
	private String networkArchitecture;
	
	/**
	 * @return Returns the methodInfo.
	 */
	public AboutTrainingMethod getMethodInfo() {
		return methodInfo;
	}
	/**
	 * @param methodInfo The methodInfo to set.
	 */
	public void setMethodInfo(AboutTrainingMethod methodInfo) {
		this.methodInfo = methodInfo;
	}
	/**
	 * @return Returns the neuralNetwork.
	 */
	public INeuralNetwork getNeuralNetwork() {
		return neuralNetwork;
	}
	/**
	 * @param neuralNetwork The neuralNetwork to set.
	 */
	public void setNeuralNetwork(INeuralNetwork neuralNetwork) {
		this.neuralNetwork = neuralNetwork;
	}
	
	
	/**
	 * @return Returns the statisticalResults.
	 */
	public StatisticalResults getStatisticalResults() {
		return statisticalResults;
	}
	/**
	 * @param statisticalResults The statisticalResults to set.
	 */
	public void setStatisticalResults(StatisticalResults statisticalResults) {
		this.statisticalResults = statisticalResults;
	}
	/**
	 * @return Returns the inputNormalization.
	 */
	public INormalization getInputNormalization() {
		return inputNormalization;
	}
	/**
	 * @param inputNormalization The inputNormalization to set.
	 */
	public void setInputNormalization(INormalization inputNormalization) {
		this.inputNormalization = inputNormalization;
	}
	/**
	 * @return Returns the outputNormalization.
	 */
	public INormalization getOutputNormalization() {
		return outputNormalization;
	}
	/**
	 * @param outputNormalization The outputNormalization to set.
	 */
	public void setOutputNormalization(INormalization outputNormalization) {
		this.outputNormalization = outputNormalization;
	}
	/**
	 * @return Returns the date.
	 */
	public Date getDate() {
		return date;
	}
	/**
	 * @param date The date to set.
	 */
	public void setDate(Date date) {
		this.date = date;
	}
	/**
	 * @return Returns the networkArchitecture.
	 */
	public String getNetworkArchitecture() {
		return networkArchitecture;
	}
	/**
	 * @param networkArchitecture The networkArchitecture to set.
	 */
	public void setNetworkArchitecture(String networkArchitecture) {
		this.networkArchitecture = networkArchitecture;
	}
} // NeuralModel