一种优化迭代权因子的组合代理模型构建方法

代理模型常被用来取代复杂工程问题中的仿真模型。为了提高代理模型的效率、精度和鲁棒性,提出一种优化迭代权因子的组合代理模型构建方法。首先采用留一交叉验证策略和预测平方和P来计算初始权因子,然后对权因子进行迭代,并在每次迭代的过程中对其进行更新,直至最终得到的组合代理模型达到理想的预测精度。为了验证该方法的有效性,对3个基准问题和1个工程实例构建了3种元模型和5种组合代理模型,并从效率、精度和鲁棒性等方面进行性能比较。结果表明本文所提出的方法不仅能得到高精度和高鲁棒性的代理模型,而且能有效缩短模型的构建时间。

Optimal Iterative Weight Factors Method for Constructing Ensemble of Surrogate Model

Surrogate models are often used to replace expensive simulation models in complicated engineering problems. The common practice is to construct multiple metamodels based on a common training data set, evaluate the accuracy, and then use only a single model perceived as the best while discarding the rest. This practice has some shortcomings as it does not take full advantage of the resources devoted to constructing different metamodels and increases the risk of adopting an inappropriate model. However, ensemble technique is an effective way to make up for the shortfalls of traditional strategy. In order to improve the efficiency, accuracy and robustness of the surrogate model, an optimal iterative weight factors method for constructing ensemble of surrogate model was proposed. At first, the leave one out cross validation strategy and PRESS criterion were presented to calculate initial weight factors. Then, an iterative process for the weight factors was conducted and at the same time the weight factors were updated until an ideal prediction accuracy of the ultimate ensemble of surrogate model was reached. To evaluate the effectiveness of the proposed method, three meta models and five ensembles of surrogate model for three benchmark problems and an engineering problem were constructed to compare their performances of efficiency, accuracy and robustness. Results show that the proposed method can not only get a higher accuracy and robustness surrogate, but also shorten the time of constructing surrogate model evidently.