ai.java.svn-base

AI大作业实现神经网络的小程序

package aihomework;

import java.io.*;
import java.nio.*;
import java.util.*;
import neuralnetworks.*;
import parameter.*;

public class AI {

	public String trainFile = "TrainingData.txt";

	public final static String aiMod = "AI_HW_MOD";

	NeuralNetwork myNN;

	double[][] trainSet;

	double[] labelSet;

	FindBest myBest;

	public AI() {
		myNN = new MultiClassNeuralNetwork(3, 6, 6, 0.3, 6);
	}

	public AI(String modName) {
		myNN = new MultiClassNeuralNetwork();
		myNN.loadNet();
	}

	public void parse() {
		try {
			BufferedReader br = new BufferedReader(new InputStreamReader(
					new FileInputStream(trainFile)));
			Vector<String> str = new Vector<String>();
			while (true) {
				String s = br.readLine();
				if (s == null)
					break;
				str.add(s);
			}
			int len=str.size();
			//int len = 10;
			trainSet = new double[len][];
			labelSet = new double[len];
			for (int i = 0; i < len; i++) {
				trainSet[i] = new double[6];
				String s = str.get(i);

				int id = 0;
				int j;
				for (j = 0; s.charAt(j) == ' '; j++)
					;
				for (; j < s.length();) {
					int k;
					for (k = j + 1; k < s.length() && s.charAt(k) != ' '; k++)
						;
					if (id == 6)
						labelSet[i] = Double.valueOf(s.substring(j, k)) - 1;
					else
						trainSet[i][id++] = Double.valueOf(s.substring(j, k));
					j = k + 1;
					for (; j < s.length() && s.charAt(j) == ' '; j++)
						;
				}
			}

		} catch (Exception e) {
			e.printStackTrace();
		}
	}

	public void run() {
		parse();
		FindBest myFind = new FindBest(myNN, trainSet, labelSet, aiMod);

		myFind.run();
	}

	public static void main(String args[]) {
		//AI ai = new AI(aiMod);
		AI ai=new AI();

		ai.run();
	}
}