//====================================================================================
public List <Case> FindAlternative_NonClustering(Case problem, string sim)
{
List <Case> NonClusterdArrCases = new List <Case>();
DefaultEngine _engine = new DefaultEngine();
Db.set_xml(sim, casename, tablename);
ArrayList myarr = Db.get_cases_as_arraylist_condition(standrize_table, casename);
// get particular cluster
_engine.SetEnvironmentVariable(_env);
_engine.SetProblem(problem);
_engine.Startup();
ArrayList cases = _engine.Run_caseRetrieval_partial(myarr);
int count_solution = cases.Count;
if (count_solution != 0)
{
Stat ss = null;
Case cc = null;
for (int i = 0; i < cases.Count; i++)
{
ss = (Stat)(cases[i]);
cc = ss.GetCBRCase();
NonClusterdArrCases.Add(cc);
}
}
return(NonClusterdArrCases);
}
//=================================================================================
public List <Case> FindAlternative_SMF(Case problem, string sim)
{
List <Case> ClusterdArrCases = new List <Case>();
DefaultEngine _engine = new DefaultEngine();
Db.set_xml(sim, casename, tablename);
// centroids = new List<Case>();
Kmeans kmeans = new Kmeans();
ArrayList current_cases_partial = new ArrayList();
// get centroids
//centroids = Db.get_Centroids(standrize_table, casename);
// know which cluster
ClusterdArrCases = new List <Case>();
current_cases_partial.Clear();
int t = kmeans.findCluster_customize(problem, centroids);
// get particular cluster
current_cases_partial = Db.get_cases_condition_cluster_arraylist(standrize_table, casename, "cluster", t.ToString());
_engine.SetEnvironmentVariable(_env);
_engine.SetProblem(problem);
// Run the reasoning engine
_engine.Startup();
ArrayList mcases = _engine.Run_caseRetrieval_partial(current_cases_partial);
int count_solution = mcases.Count;
if (count_solution != 0)
{
Stat ss = null;
Case cc = null;
for (int i = 0; i < mcases.Count; i++)
{
ss = (Stat)(mcases[i]);
cc = ss.GetCBRCase();
ClusterdArrCases.Add(cc);
}
}
return(ClusterdArrCases);
}
