📄 equation.cs
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newRow["blm"] = blm;
newRow["code"] = 1;
dt.Tables[dt.Tables[0].ToString()].Rows.Add(newRow);
}
}
public void get_GDITOGDP2C(DataSet ds, DataSet dt, string blm, float start_rate, float over_rate)
{
int Count_R = ds.Tables[0].Rows.Count;//ds的行数
int Count_C = ds.Tables[0].Columns.Count;//ds的列数
int dt_Count_C = dt.Tables[0].Columns.Count;//读取dt的列数
//定义变量
int i, j;
int Rate_num = 1;
float rate_data = start_rate;
//定义数组
float[,] values = new float[Count_R + 3, Count_C];//这里加3是因为,需要预测未来三年的数据
float[] rate = new float[11];
//计算变化率的个数
rate[0] = 0;
for (i = 1; i < Convert.ToInt16(2 * (over_rate * 100 - start_rate * 100 + 1) + 1); i++)
{
Rate_num = Rate_num + 1;
if (i % 2 == 1)
rate[i] = -1 * rate_data;
if (i % 2 == 0)
{
rate[i] = rate_data;
rate_data = Convert.ToSingle(rate_data + 0.01);
}
}
//读取ds数据集里的数据到values数组中
for (i = 0; i < Count_R; i++)
for (j = 0; j < Count_C; j++)
values[i, j] = Convert.ToSingle(ds.Tables[0].Rows[i][j].ToString());
//用移动平均法计算未来三年的数据
for (i = Count_R; i < (Count_R + 3); i++)
{
values[i, 0] = values[i - 1, 0] + 1;
for (j = 1; j < Count_C; j++)
{
values[i, j] = (values[i - 3, j] + values[i - 2, j] + values[i - 1, j]) / 3;
}
}
//开始计算数据
float[,] data = new float[Rate_num, dt_Count_C];
for (i = 0; i < Rate_num; i++)
{
data[i, 0] = rate[i];
for (j = 1; j < dt_Count_C - 2; j++)
{
values[j - 1, 1] = Convert.ToSingle(values[j - 1, 1] * (1 - rate[i]));
data[i, j] = Convert.ToSingle(0.199994 * values[j - 1, Count_C - 7] - 0.0106 * values[j - 1, Count_C - 6] + 0.130277 * values[j - 1, Count_C - 5] + 0.084486 * values[j - 1, Count_C - 4] + 0.053933 * values[j - 1, Count_C - 3] + 0.292656 * values[j - 1, Count_C - 2] + 0.194537 * values[j - 1, Count_C - 1] + 7.126996);
}
}
//把数据存储到dt数据集里面
for (i = 0; i < Rate_num; i++)
{
DataRow newRow = dt.Tables[dt.Tables[0].ToString()].NewRow();
newRow["rate"] = Math.Round(rate[i], 2);
for (j = 1; j < dt_Count_C - 2; j++)
newRow["year" + j] = data[i, j];
newRow["blm"] = blm;
newRow["code"] = 1;
dt.Tables[dt.Tables[0].ToString()].Rows.Add(newRow);
}
}
public void get_GDITOGDP3(DataSet ds, DataSet dt, string blm, float start_rate, float over_rate)
{
int Count_R = ds.Tables[0].Rows.Count;//ds的行数
int Count_C = ds.Tables[0].Columns.Count;//ds的列数
int dt_Count_C = dt.Tables[0].Columns.Count;//读取dt的列数
//定义变量
int i, j;
int Rate_num = 1;
float rate_data = start_rate;
//定义数组
float[,] values = new float[Count_R + 3, Count_C];//这里加3是因为,需要预测未来三年的数据
float[] rate = new float[11];
//计算变化率的个数
rate[0] = 0;
for (i = 1; i < Convert.ToInt16(2 * (over_rate * 100 - start_rate * 100 + 1) + 1); i++)
{
Rate_num = Rate_num + 1;
if (i % 2 == 1)
rate[i] = -1 * rate_data;
if (i % 2 == 0)
{
rate[i] = rate_data;
rate_data = Convert.ToSingle(rate_data + 0.01);
}
}
//读取ds数据集里的数据到values数组中
for (i = 0; i < Count_R; i++)
for (j = 0; j < Count_C; j++)
values[i, j] = Convert.ToSingle(ds.Tables[0].Rows[i][j].ToString());
//用移动平均法计算未来三年的数据
for (i = Count_R; i < (Count_R + 3); i++)
{
values[i, 0] = values[i - 1, 0] + 1;
for (j = 1; j < Count_C; j++)
{
values[i, j] = (values[i - 3, j] + values[i - 2, j] + values[i - 1, j]) / 3;
}
}
//开始计算数据
float[,] data = new float[Rate_num, dt_Count_C];
for (i = 0; i < Rate_num; i++)
{
data[i, 0] = rate[i];
for (j = 1; j < dt_Count_C - 2; j++)
{
values[j - 1, 1] = Convert.ToSingle(values[j - 1, 1] * (1 - rate[i]));
data[i, j] = Convert.ToSingle(0.015852 * values[j - 1, Count_C - 8] + 0.259172 * values[j - 1, Count_C - 7] + 0.010543 * values[j - 1, Count_C - 6] + 0.154584 * values[j - 1, Count_C - 5] - 0.0028 * values[j - 1, Count_C - 4] + 0.182909 * values[j - 1, Count_C - 3] + 0.09659 * values[j - 1, Count_C - 2] + 0.135994 * values[j - 1, Count_C - 1] + 16.63879);
}
}
//把数据存储到dt数据集里面
for (i = 0; i < Rate_num; i++)
{
DataRow newRow = dt.Tables[dt.Tables[0].ToString()].NewRow();
newRow["rate"] = Math.Round(rate[i], 2);
for (j = 1; j < dt_Count_C - 2; j++)
newRow["year" + j] = data[i, j];
newRow["blm"] = blm;
newRow["code"] = 1;
dt.Tables[dt.Tables[0].ToString()].Rows.Add(newRow);
}
}
public void get_GDITOPCDI(DataSet ds, DataSet dt, string blm, float start_rate, float over_rate)
{
int Count_R = ds.Tables[0].Rows.Count;//ds的行数
int Count_C = ds.Tables[0].Columns.Count;//ds的列数
int dt_Count_C = dt.Tables[0].Columns.Count;//读取dt的列数
//定义变量
int i, j;
int Rate_num = 1;
float rate_data = start_rate;
//定义数组
float[,] values = new float[Count_R + 3, Count_C];//这里加3是因为,需要预测未来三年的数据
float[] rate = new float[11];
//计算变化率的个数
rate[0] = 0;
for (i = 1; i < Convert.ToInt16(2 * (over_rate * 100 - start_rate * 100 + 1) + 1); i++)
{
Rate_num = Rate_num + 1;
if (i % 2 == 1)
rate[i] = -1 * rate_data;
if (i % 2 == 0)
{
rate[i] = rate_data;
rate_data = Convert.ToSingle(rate_data + 0.01);
}
}
//读取ds数据集里的数据到values数组中
for (i = 0; i < Count_R; i++)
for (j = 0; j < Count_C; j++)
values[i, j] = Convert.ToSingle(ds.Tables[0].Rows[i][j].ToString());
//用移动平均法计算未来三年的数据
for (i = Count_R; i < (Count_R + 3); i++)
{
values[i, 0] = values[i - 1, 0] + 1;
for (j = 1; j < Count_C; j++)
{
values[i, j] = (values[i - 3, j] + values[i - 2, j] + values[i - 1, j]) / 3;
}
}
//开始计算数据
float[,] data = new float[Rate_num, dt_Count_C];
for (i = 0; i < Rate_num; i++)
{
data[i, 0] = rate[i];
for (j = 1; j < dt_Count_C - 2; j++)
{
values[j - 1, 1] = Convert.ToSingle(values[j - 1, 1] * (1 - rate[i]));
data[i, j] = Convert.ToSingle(-0.00791 * values[j - 1, Count_C - 9] + 0.107765 * values[j - 1, Count_C - 8] + 0.923757 * values[j - 1, Count_C - 7] - 0.03073 * values[j - 1, Count_C - 6] + 0.126538 * values[j - 1, Count_C - 5] + 0.073282 * values[j - 1, Count_C - 4] - 0.04729 * values[j - 1, Count_C - 3] - 0.0888 * values[j - 1, Count_C - 2] - 0.14015 * values[j - 1, Count_C - 1] + 8.448927);
}
}
//把数据存储到dt数据集里面
for (i = 0; i < Rate_num; i++)
{
DataRow newRow = dt.Tables[dt.Tables[0].ToString()].NewRow();
newRow["rate"] = Math.Round(rate[i], 2);
for (j = 1; j < dt_Count_C - 2; j++)
newRow["year" + j] = data[i, j];
newRow["blm"] = blm;
newRow["code"] = 1;
dt.Tables[dt.Tables[0].ToString()].Rows.Add(newRow);
}
}
public void get_GDITOTLM(DataSet ds, DataSet dt, string blm, float start_rate, float over_rate)
{
int Count_R = ds.Tables[0].Rows.Count;//ds的行数
int Count_C = ds.Tables[0].Columns.Count;//ds的列数
int dt_Count_C = dt.Tables[0].Columns.Count;//读取dt的列数
//定义变量
int i, j;
int Rate_num = 1;
float rate_data = start_rate;
//定义数组
float[,] values = new float[Count_R + 3, Count_C];//这里加3是因为,需要预测未来三年的数据
float[] rate = new float[11];
//计算变化率的个数
rate[0] = 0;
for (i = 1; i < Convert.ToInt16(2 * (over_rate * 100 - start_rate * 100 + 1) + 1); i++)
{
Rate_num = Rate_num + 1;
if (i % 2 == 1)
rate[i] = -1 * rate_data;
if (i % 2 == 0)
{
rate[i] = rate_data;
rate_data = Convert.ToSingle(rate_data + 0.01);
}
}
//读取ds数据集里的数据到values数组中
for (i = 0; i < Count_R; i++)
for (j = 0; j < Count_C; j++)
values[i, j] = Convert.ToSingle(ds.Tables[0].Rows[i][j].ToString());
//用移动平均法计算未来三年的数据
for (i = Count_R; i < (Count_R + 3); i++)
{
values[i, 0] = values[i - 1, 0] + 1;
for (j = 1; j < Count_C; j++)
{
values[i, j] = (values[i - 3, j] + values[i - 2, j] + values[i - 1, j]) / 3;
}
}
//开始计算数据
float[,] data = new float[Rate_num, dt_Count_C];
for (i = 0; i < Rate_num; i++)
{
data[i, 0] = rate[i];
for (j = 1; j < dt_Count_C - 2; j++)
{
values[j - 1, 1] = Convert.ToSingle(values[j - 1, 1] * (1 - rate[i]));
data[i, j] = Convert.ToSingle(-0.00285 * values[j - 1, Count_C - 9] + 0.049985 * values[j - 1, Count_C - 8] + 0.014962 * values[j - 1, Count_C - 7] + 0.02649 * values[j - 1, Count_C - 6] + 0.030702 * values[j - 1, Count_C - 5] - 0.03301 * values[j - 1, Count_C - 4] + 0.164334 * values[j - 1, Count_C - 3] + 0.002218 * values[j - 1, Count_C - 2] + 0.332498 * values[j - 1, Count_C - 1] + 40.82747);
}
}
//把数据存储到dt数据集里面
for (i = 0; i < Rate_num; i++)
{
DataRow newRow = dt.Tables[dt.Tables[0].ToString()].NewRow();
newRow["rate"] = Math.Round(rate[i], 2);
for (j = 1; j < dt_Count_C - 2; j++)
newRow["year" + j] = data[i, j];
newRow["blm"] = blm;
newRow["code"] = 1;
dt.Tables[dt.Tables[0].ToString()].Rows.Add(newRow);
}
}
public void get_data2(DataSet ds, DataSet dt, string blm, float start_rate, float over_rate)
{
switch (blm)
{
case "C_GDP":
get_CGTOGDP(ds, dt, blm, start_rate,over_rate); break;
case "C_CP":
get_CGTOCP(ds, dt, blm, start_rate, over_rate); break;
case "C_DI":
get_CGTODI(ds, dt, blm, start_rate, over_rate); break;
case "C_GDI":
get_CGTOGDI(ds, dt, blm, start_rate, over_rate); break;
default:
get_CGTOGDP(ds, dt, blm, start_rate, over_rate); break;
}
}//政府消费的选择函数
public void get_CGTOGDP(DataSet ds, DataSet dt, string blm, float start_rate, float over_rate)
{
int Count_R = ds.Tables[0].Rows.Count;//ds的行数
int Count_C = ds.Tables[0].Columns.Count;//ds的列数
int dt_Count_C = dt.Tables[0].Columns.Count;//读取dt的列数
//定义变量
int i, j;
int Rate_num = 1;
float rate_data = start_rate;
//定义数组
float[,] values = new float[Count_R + 3, Count_C];//这里加3是因为,需要预测未来三年的数据
float[] rate = new float[11];
//计算变化率的个数
rate[0] = 0;
for (i = 1; i < Convert.ToInt16(2 * (over_rate * 100 - start_rate * 100 + 1) + 1); i++)
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