2. Data Model 2.1 Linear Programmin

2. Data Model

2.1 Linear Programming Model

Consist of three parts.
1. Decision Variable
2. Objective function
3. Constrains

2.2 Time Series Model (one type of model in Prediction Model)

Time Series Data
1. Trend (T)
2. Seasonal Variation (S)
3. Cyclical Variation (C)
4. Irregular Variation (L)
*In our project we decide to do a cyclical variation because amount of employees’ task maybe depend on economic*
In the Cyclical Variation there are four stages of analysis;
1. Economic Prosperity
2. Economic Recession
3. Economic Depression
4. Economic Recovery

ผลลัพธ์ (อังกฤษ) 2:

2. Data Model 2.1 Linear Programming Model Consist of Three Parts. 1. Variable decision 2. Objective function 3. Constrains 2.2 Time Series Model (one Type of Model in Prediction Model) Time Series Data 1. Trend (T) 2. Seasonal Variation (S) 3. Variation cyclical (C) 4. Irregular Variation (L) * In our Project because we Decide to do a cyclical variation amount of employees' Depend on Economic Task maybe * In the Cyclical Variation there are Four Stages of Analysis; 1. Economic Prosperity 2. Economic Recession 3. Economic Depression 4. Economic Recovery

ผลลัพธ์ (อังกฤษ) 3:

2. Data Model

2.1 Linear Programming Model

Consist of three parts.
1. Decision Variable
2. Objective 3. Constrains function

.
2.2 Time Series Model (one type of model in Prediction Model)

Time Series Data
1. Trend (T)
2. Seasonal Variation (S)
3.? Cyclical Variation (C)
4. Irregular Variation (L)
.* In our project we decide to do a cyclical variation because amount of employees' task maybe depend on economic *
In the. Cyclical Variation there are four stages of analysis;
1. Economic Prosperity
2. Economic Recession
3. Economic Depression
4.? Economic Recovery
.