Multi-layer weighted grey principal component evaluation model and its application

Considering the lack of primitive variables and samples, which exists objectively in the evaluation practice, the multi-layer weighted grey principal component evaluation model is constructed. Firstly, the normalized importance weights are assigned to the subsystem of the evaluation system and the corresponding indices respectively under the premise that all of them are established scientifically. On that basis, the weighted normalized matrix for evaluation is generated to calculate the grey similitude correlation degree matrix, and the principal component scores of each evaluation subsystem are calculated based on it instead of the traditional correlation matrix. Then, the final evaluation basis is obtained through weighting the scores of each evaluation subsystem by their importance weights. Finally, performances of thermal power generation units are analyzed comparatively by using different evaluation models including the proposed model. Theoretical research and case analysis demonstrate that the proposed model is scientific, effective and more suitable in these situations where there are insufficient evaluation variables, or the sample size is small, as well as there may be a non-linear correlation between evaluation indicators. © 2019, Editorial Office of Control and Decision. All right reserved.