NEROControllerImp, 神经网络索引类
package OEI.ME.nero.E;
import java.util.Map;
import AVQ.ASQ.OVQ.OSQ.VSQ.obj.FMHMMNode;
import SVQ.stable.StablePOS;
import OCI.ME.nero.C.NERO_C;
//作者，著作权人： 罗瑶光， 浏阳。
public class NERO_CE implements NERO_C {
  @SuppressWarnings({StablePOS.RAW_TYPES, StablePOS.UNCHECKED})
  public StringBuilder getBinaryForestRecurWord(StringBuilder outputWordNode
  , String inputString, int charPosition
      , int inputStringLength, Map<Integer, Map> forestRoots
      , int forestDepth, int charPositionNext ) {
    if (StablePOS.INT_THREE== forestDepth) {
      return outputWordNode;
    }
    char charAtPosition= inputString.charAt(charPosition);
    int rangeHigh= charAtPosition>> StablePOS.INT_TEN;
    Map<Integer, Map> trees= forestRoots.get(rangeHigh);
    if (null== trees) {
      return outputWordNode;
    }
    int range= charAtPosition>> StablePOS.INT_SIX;
    if (!trees.containsKey(range)) {
      return outputWordNode;
    }
    Map<Long, FMHMMNode> maps= trees.get(range);
    FMHMMNode fFHMMNode= maps.get(Long.valueOf(charAtPosition));
    if (null== fFHMMNode) {
      return outputWordNode;
    }
    Map<String, Integer> outputList= fFHMMNode.getNext();
    if (null== outputList||charPositionNext>= inputStringLength) {
      return outputWordNode;
    }
    char positionOfi= inputString.charAt(charPositionNext);
    if (outputList.containsKey(String.valueOf(positionOfi))) {
      outputWordNode= getBinaryForestRecurWord(outputWordNode
      .append(positionOfi), inputString
          , charPositionNext, inputStringLength, forestRoots
          , forestDepth+ StablePOS.INT_ONE, ++charPositionNext);
    }
    return outputWordNode;
  }
}