public DecisionMatrixDisplayForm(DecisionMatrix decisionMatrix, Standardize standardize)
: this()
{
_decisionMatrix = decisionMatrix;
_standardize = standardize;
Init();
}
public DecisionMatrixForm(DecisionMatrix decisionMatrix)
{
InitializeComponent();
//将决策矩阵中的数据转化为专家列表
_decisionMatrix = decisionMatrix;
_experts = decisionMatrix.ToExpertList();
dataGrid.DataSource = _experts;
}
public static DecisionMatrix ApprovedNormalize(DecisionMatrix toBeStandardize)
{
//归一化之后的矩阵
DecisionMatrix standardized = new DecisionMatrix(toBeStandardize.Level, toBeStandardize.X);
//将原始数据头填充到新数据中，所有操作都不改变原来的判断矩阵
standardized.InsertFromMatrix(toBeStandardize);
var factors = toBeStandardize.Level.Factors;
int m = standardized.X;
//标准化按照指标值，逐列进行的
for (int j = 0; j < factors.Count; j++)
{
//每一列的最大值和最小值
double columnMax = toBeStandardize.GetColumnMaxValue(j);
double columnMin = toBeStandardize.GetColumnMinValue(j);
//1. 如果是逆向指标，就执行
if (factors[j].Direction == FactorDirection.Negative)
{
for (int i = 0; i < toBeStandardize.X; i++)
{
standardized[i, j] = columnMax - toBeStandardize[i, j] + columnMin;
}
}
//2. 如果指标值包含负数，就执行
bool containsNegative = false;
for (int i = 0; i < standardized.X; i++)
{
if (standardized[i, j] < 0)
{
containsNegative = true;
break;
}
}
//如果包含负数
if (containsNegative)
{
for (int i = 0; i < standardized.X; i++)
{
standardized[i, j] = standardized[i, j] - columnMin;
}
}
//3. 执行标准的归一化操作
//考虑到如果m太大，会造成标准化之太小，所以统一都乘以m
double columnSum = standardized.GetColumnSum(j);
for (int i = 0; i < standardized.X; i++)
{
standardized[i, j] = (standardized[i, j] / columnSum) * m;
}
}
return standardized;
}
//构造函数
public MainWindow()
{
InitializeComponent();
//默认不使用改进的方式
isApproved = false;
judgeMatrixSwitchBtn.Text = "常规构造";
//初始化层次结构模型
InitModel();
//初始化决策矩阵
_decisionMatrix = new DecisionMatrix(_ahpModel.Levels[2], 0);
//初始化判断矩阵
InitJudgeMatrixPairs();
//更新模型中的判断矩阵
UpdateJudgeMatrix();
}
public static void AhpModelSample()
{
//创建第一层
Level topLevel = new Level(null,
new List<Factor> { new Factor("Z") },
null,
null);
//实例化一个AhpModel，并设置第一层对象
AhpModel ahpModel = new AhpModel(topLevel);
//插入一个层次，直到用户表示不再增减
while (true)
{
//默认插入第二层
InsertLevel(ahpModel);
//然后询问是否继续插入其他层次
var ifAddLevel = DataHelper.ReadBool("是否插入一个层次");
if (!ifAddLevel)
break;
}
//打印层次结构模型中的相关信息
ahpModel.DisplayModelInfo();
//选择用以生成决策矩阵的层次
//读入的数要-1
int selectLevel = DataHelper.ReadValus<int>(string.Format("请从第1层到第{0}层中选择一层来创建决策矩阵", ahpModel.Levels.Count))[0] - 1;
//选择待评价的元素
int elementCount = DataHelper.ReadValus<int>("请问一共有多少待评价元素？")[0];
//建立空的决策矩阵
DecisionMatrix decisionMatrix = new DecisionMatrix(ahpModel.Levels[selectLevel], elementCount, "决策矩阵");
//读入决策矩阵数据
decisionMatrix.InsertMatrix(DataHelper.ConsoleArrayInput);
//打印决策矩阵
decisionMatrix.DisplayMatrix(DataHelper.ConsoloOutput);
//使用改进的标准化方法处理决策矩阵
Console.WriteLine("使用改进的归一化法对决策矩阵进行标准化法");
ManipulateDecisionMatrix(decisionMatrix, Standardizer.ApprovedNormalize);
//使用常规归一化法处理决策矩阵
Console.WriteLine("使用常规的归一化法对决策矩阵进行标准化");
ManipulateDecisionMatrix(decisionMatrix, Standardizer.Normalize);
}
public static DecisionMatrix Normalize(DecisionMatrix toBeStandardize)
{
//归一化之后的矩阵
DecisionMatrix standardized = new DecisionMatrix(toBeStandardize.Level, toBeStandardize.X);
//将原始数据头填充到新数据中，所有操作都不改变原来的判断矩阵
standardized.InsertFromMatrix(toBeStandardize);
var factors = toBeStandardize.Level.Factors;
for (int j = 0; j < factors.Count; j++)
{
//执行标准的归一化操作
//获取一列的和
double columnSum = standardized.GetColumnSum(j);
for (int i = 0; i < standardized.X; i++)
{
standardized[i, j] = (standardized[i, j] / columnSum);
}
}
return standardized;
}
//将ExpertList的数据导入到决策矩阵中
public static DecisionMatrix SetDecisionMatrix(this DecisionMatrix decisionMatrix, IList<ExpertModel> expertModels)
{
DecisionMatrix newDecisionMatrix = new DecisionMatrix(decisionMatrix.Level, expertModels.Count);
for (int i = 0; i < expertModels.Count; i++)
{
newDecisionMatrix[i, 0] = expertModels[i].B1;
newDecisionMatrix[i, 1] = expertModels[i].B2;
newDecisionMatrix[i, 2] = expertModels[i].B3;
newDecisionMatrix[i, 3] = expertModels[i].B4;
newDecisionMatrix[i, 4] = expertModels[i].B5;
newDecisionMatrix[i, 5] = expertModels[i].B6;
newDecisionMatrix[i, 6] = expertModels[i].B7;
newDecisionMatrix[i, 7] = expertModels[i].B8;
newDecisionMatrix[i, 8] = expertModels[i].B9;
newDecisionMatrix[i, 9] = expertModels[i].B10;
newDecisionMatrix[i, 10] = expertModels[i].B11;
newDecisionMatrix[i, 11] = expertModels[i].B12;
newDecisionMatrix[i, 12] = expertModels[i].B13;
newDecisionMatrix[i, 13] = expertModels[i].B14;
}
return newDecisionMatrix;
}
//响应决策矩阵的修改
private void OnDcsMatrixUpdate(DecisionMatrix decisionMatrix)
{
_decisionMatrix = decisionMatrix;
}
//处理决策矩阵，打印出决策矩阵的标准化值，以及最终的决策向量
public static void ManipulateDecisionMatrix(DecisionMatrix decisionMatrix, Standardize standardize)
{
//获得并打印标准化矩阵
var standardized = decisionMatrix.GetStandardized(standardize);
standardized.Name = "决策矩阵的标准化矩阵";
standardized.DisplayMatrix(DataHelper.ConsoloOutput);
//获得决策向量
var decisionVect = decisionMatrix.GetDecisionVect(standardize);
//打印决策结果
decisionVect.DisplayMatrix(DataHelper.ConsoloOutput);
}
//保存按钮
//只能在这里修改决策矩阵！！
private void saveBtn_Click(object sender, EventArgs e)
{
_decisionMatrix = _decisionMatrix.SetDecisionMatrix(_experts);
DecisionMatrixSave(_decisionMatrix);
Close();
}
