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中文摘要：
提高序贯近似建模的精度和收敛效率,关键在于制定合理有效的序贯抽样准则。针对如何有效获取目标系统信息进行近似建模,同时提高建模精度和收敛效率,提出了基于部分交叉验证的多准则序贯近似建模方法。通过融合部分交叉验证误差估计准则、极大序贯建模累积变化准则和极大熵准则的特征和优势,可实现对全空间全面抽样和对不规则区域重点抽样,进而提高近似模型的精度和收敛效率。算例测试表明该方法在提高序贯近似建模精度和收敛效率方面可行有效。
英文摘要：
The key technique of improving sequential approximation modeling accuracy and convergence efficiency is to establish reasonable and efficient sequential sampling criteria.To obtain target system information effectively and accelerate convergence of modeling accuracy,a multi-criterion sequential modeling method based on partial cross validation is proposed.By combination of partial cross validation error estimation criterion,maximum sequential modeling accumulation change criterion and maximum entropy criterion,the space-filled sampling and irregular region importance sampling are realized,and approximation accuracy and convergence efficiency are improved.Test examples validate the feasibility and efficacy of this method.
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