化工学报2016，Vol.67Issue(3)：820-826,7.DOI:10.11949/j.issn.0438-1157.20151921
一种新颖的小样本整体趋势扩散技术
A novel mega-trend-diffusion for small sample
摘要
Abstract
Process modeling, optimization and control methods based on data-driven attract attention to both academic community and business circles in terms of its research domains and applications. Even in Big Data era, small sample problems cannot be ignored. In view of the difficulty of obtaining high learning accuracy with small-sample-set using traditional modeling methods, such as artificial neural networks (ANNs), extreme learning machine (ELMs),etc., a novel technology of multi-distribution mega-trend-diffusion (MD-MTD) is proposed to improve the learning accuracy of small-sample-set. The mega-trend-diffusion (MTD) is employed to estimate the acceptable range of the attribution of small sample. The uniform distribution and triangular distribution are added based on MTD to describe data characteristics, which are used to generate virtual samples and fill information gaps among observations in small sample. A benchmarking function is utilized to generate benchmarking samples under the orthogonal test and inhomogeneous sample test in order to verify the reasonability and effectiveness of the MD-MTD, and two industrial real-world datasets include MLCC and PTA are used to further confirm the practicability of the MD-MTD. The results of the validation tests manifest that the proposed MD-MTD can improve the learning accuracy of more than 8% for small sample.关键词
小样本集/整体趋势扩散技术/虚拟样本/正交实验Key words
small-sample-set/mega-trend-diffusion/virtual sample/orthogonal test分类
信息技术与安全科学引用本文复制引用
朱宝,陈忠圣,余乐安..一种新颖的小样本整体趋势扩散技术[J].化工学报,2016,67(3):820-826,7.基金项目
国家自然科学基金项目（71433001）。@@@@supported by the National Natural Science Foundation of China(71433001) （71433001）
