Subjective Complexity Measurement Model for Emergency Repair Based on Improved Weight Support Vector Regression Model

To improve the objective complexity's inaccurate and less effective in estimating the time and training requirement analyzing, the subjective complexity is introduced. The external, subjective factors such as environment, personal ability is applied to establish the rush repair subjective complexity measurement model by combing weight with support vector which is called improved weight support vector regression model (IWSVR). To solve this model high efficiently, the genetic algorithm meothod which is crossed and viated by cloud model is introduced. Then, the model is validated by the correlativity between the subjective complexity and personal performance (time). The result proves that both the generalization ability and accuracy are better than normal SVR model in personal time estimating and the subjective complexity is better than objective complexity in predicting the personal performance.