public override ILearnAlgorithmConf getConf(int CountFeatures)
{
ILearnAlgorithmConf result = new ESConfig();
result.Init(CountFeatures);
return(result);
}
/// <summary>
/// 获取客户端
/// </summary>
/// <param name="esConfig"></param>
/// <returns></returns>
public ElasticClient GetClient(ESConfig esConfig)
{
var uris = esConfig.Urls.Split(',').ToList().Select(i => Uri.TryCreate(i, UriKind.Absolute, out Uri u) ? u : null); //配置节点地址，以，分开
var settings = new ConnectionSettings(new StaticConnectionPool(uris))
.BasicAuthentication(esConfig.User, esConfig.Pwd) //用户名和密码
.RequestTimeout(TimeSpan.FromSeconds(30)); //请求配置参数
this.Client = new ElasticClient(settings); //linq请求客户端初始化
return(this.Client);
}
protected override void fill_conf()
{
ESConfig conf1 = conf as ESConfig;
conf1.ESCInitType = type_init;
conf1.ESCMutateAlg = type_mutate;
conf1.ESCCrossoverType = type_cross;
conf1.ESCCrossoverPropability = pcross;
conf1.ESCCountCrossoverPoint = (int)cpcross;
conf1.ESCAngleRotateB = angleR;
conf1.ESCCountIteration = (int)iterate;
conf1.ESCPopulationSize = (int)cindiv;
conf1.ESCCountChild = (int)cchild;
}
public virtual void Init(ILearnAlgorithmConf Conf)
{
Config = Conf as ESConfig;
count_populate = Config.ESCPopulationSize;
count_child = Config.ESCCountChild;
count_iterate = Config.ESCCountIteration;
coef_t1 = Config.ESCT1;
coef_t2 = Config.ESCT2;
param_crossover = Config.ESCCrossoverPropability;
alg_cross = Config.ESCCrossoverType;
type_init = Config.ESCInitType;
count_Multipoint = Config.ESCCountCrossoverPoint;
type_mutate = Config.ESCMutateAlg;
b_ro = Config.ESCAngleRotateB;
main_pop = new Population(count_populate, count_child, result.CountFeatures, result.LearnSamplesSet);
main_pop.init_first(result.RulesDatabaseSet[0], rand, type_init);
}
public override int Run(string[] args)
{
Console.WriteLine("Start");
fill_params(args);
Console.WriteLine("Params get \nfile in {0} ", file_in);
Approx_learn_set = BaseUFSLoader.LoadLearnFromUFS(file_in);
Console.WriteLine("Tra load");
Approx_test_set = BaseUFSLoader.LoadTestFromUFS(file_in);
Console.WriteLine("Tst load");
conf = new ESConfig();
conf.Init(Approx_learn_set.CountVars);
fill_conf();
Console.WriteLine("Conf Filed");
Approx_Singletone = new SAFuzzySystem(Approx_learn_set, Approx_test_set);
Approx_Singletone = SAFSUFSLoader.loadUFS(Approx_Singletone, file_in);
Console.WriteLine("Classifier created");
optimaze = new ESMethod();
Approx_Singletone = optimaze.TuneUpFuzzySystem(Approx_Singletone, conf);
Console.WriteLine("Optimization complite");
SAFSUFSWriter.saveToUFS(Approx_Singletone, file_out);
Console.WriteLine("Saved");
return(1);
}
/// <summary> /// /// </summary> /// <param name="esConfig"></param> public ESService(ESConfig esConfig) => GetClient(esConfig);
private List <ILearnAlgorithmConf> initAlgoritmsConfigs(int CountFeature)
{
List <ILearnAlgorithmConf> result = new List <ILearnAlgorithmConf>();
if (isTermShrink)
{
result.Add(new OptimizeTermShrinkAndRotateConf());
}
if (isRuleShrink)
{
result.Add(new OptimizeRullesShrinkConf());
}
if (isUnionTerm)
{
result.Add(new UnionTermsConf());
}
if (isLindBreakCross)
{
result.Add(null);
}
if (isPSO)
{
for (int i = 0; i < countPSO; i++)
{
result.Add(new PSOSearchConf());
}
}
if (isANT)
{
for (int i = 0; i < countANT; i++)
{
result.Add(new MACOSearchConf());
}
}
if (isBEE)
{
for (int i = 0; i < countBEE; i++)
{
result.Add(new BeeStructureConf());
}
}
if (isES)
{
for (int i = 0; i < countES; i++)
{
ESConfig method = new ESConfig();
method.Init(CountFeature);
result.Add(method);
}
}
if (isGA)
{
for (int i = 0; i < countGA; i++)
{
GeneticConf method = new GeneticConf();
method.Init(CountFeature);
result.Add(method);
}
}
/* if (isBFO)
* {
* for (int i = 0; i < countBFO; i++)
* {
* BacterialForagingOptimization.Base.BacteryAlgorithmConfig method = new BacterialForagingOptimization.Base.BacteryAlgorithmConfig();
* method.Init(CountFeature);
* result.Add(method);
* }
* }
*/
return(result);
}
