main()
{
//创建负责读取输入的线程
DWORD ThreadID = 1, ThreadID1 = 2;
HANDLE hRead, hRead1;
initialize();//初始化数据
hMutex = CreateMutex(NULL, FALSE, NULL);//创建互斥对象
//建立两个线程
hRead = CreateThread(NULL, 0, (LPTHREAD_START_ROUTINE)getInput, NULL, 0, &ThreadID);//接受键盘输入
hRead1 = CreateThread(NULL, 0, (LPTHREAD_START_ROUTINE)IO, NULL, 0, &ThreadID1);//接受屏幕输入和dos输出
while (1)//不断重复判断电梯运行情况
{
state_trans(); //根据自动机模型和control()计算出的电梯目标楼层和运行方向决定此刻电梯的状态
control(); //根据当前策略决定此刻电梯目标楼层和运行方向
if (startexit == 1)//检测到图形界面关闭 return退出
{
return 0;
}
}
}
void HMMDataSet::read(int idAction){
openMysqlSession();
cout<<"Reading HMMData for action:"<<idAction<<endl;
this->idAction=idAction;
ResultSet *resSet;
PreparedStatement *prep_stmt;
/* create a statement object */
prep_stmt = con -> prepareStatement("SELECT * FROM `HMMDataSet` WHERE `compression_rate`=? AND `num_clusters`=? AND `id_action`=?");
prep_stmt->setInt(1, compressionRate);
prep_stmt->setInt(2, numClusters);
prep_stmt->setInt(3, idAction);
resSet = prep_stmt->executeQuery();
while (resSet->next()) {
std::stringstream state_trans(resSet->getString("state_trans"));
std::stringstream initial_state_dist(resSet->getString("initial_state_dist"));
std::stringstream obs_prob_dist(resSet->getString("obs_prob_dist"));
std::stringstream cluster_distribution(resSet->getString("cluster_distribution"));
stateTrans.resize(numStates, vector<double>(numStates, 0));
initialStateDist.resize(numStates, 0);
obsProbDist.resize(numStates, vector<double>(numStates,0));
clustDist.resize(numStates);
for (int i = 0; i < numClusters; i++) {
for (int j = 0; j < numClusters; j++) {
state_trans >> stateTrans[i][j];
}
}
for (int j = 0; j < numClusters; j++) {
initial_state_dist >> initialStateDist[j];
}
for (int i = 0; i < numClusters; i++) {
for (int j = 0; j < numClusters; j++) {
obs_prob_dist>> obsProbDist[i][j];
}
}
for (int j = 0; j < numClusters; j++) {
ClusterDistribution cluster;
cluster_distribution >> cluster.mean.idCluster;
cluster.mean.center.resize(Vector_Size);
for (int k = 0; k < Vector_Size; k++) {
cluster_distribution >> cluster.mean.center[k];
}
cluster_distribution >> cluster.standardDeviation;
clustDist.push_back(cluster);
}
}
delete resSet;
delete prep_stmt;
closeMysqlSession();
}
