影响因子：2.5
DOI码：10.32604/cmes.2025.073615
所属单位：船舶工程学院
发表刊物：CMES-Computer Modeling in Engineering & Sciences
刊物所在地：美国
项目来源：Key Research Project in Universities of Henan Province (No. 24B480012;No. 25A450004), Key Specialize
关键字：Perovskite photovoltaic cells; random forest; knowledge distillation; BiGRU-attention
摘要：Accurate prediction of perovskite photovoltaic materials’ optoelectronic properties is crucial for developing efficient and stable materials, advancing solar technology. To address poor interpretability, high computational complexity, and inaccurate predictions in relevant machine learning models, this paper proposes a novel methodology. The technical route of this paper mainly centers on the random forest-knowledge distillation-bidirectional gated recurrent unit with attention technology (namely RF-KD-BIGRUA), which is applied in perovskite photovoltaic materials. Primarily, it combines random forest to quantitatively assess feature importance, selecting variables with significant impacts on photoelectric conversion efficiency. Subsequently, statistical techniques analyze the weight distribution of variables influencing power conversion efficiency (PCE, %) to extract key features. In the model optimization phase, knowledge distillation transfers features from complex teacher models to student models, enhancing prediction accuracy. Additionally, Bidirectional Gated Recurrent Unit with Attention technology (BiGRU-Attention) is introduced to further optimize predictive performance while substantially reducing computational costs. The results demonstrate that integrating statistical techniques into intelligent optimization models can quantify photovoltaic system uncertainties and reduce prediction errors before experimental fabrication, enabling efficient pre-fabrication screening of perovskite materials that meet energy-storage criteria and providing accurate guidance for material selection.
备注：Key Research Project in Universities of Henan Province (No. 24B480012;No. 25A450004), Key Specialized Research andDevelopment Breakthrough Program in Henan Province (No. 242102240051)
合写作者：钱佳晶,彭丽玲,贾欣航,Ling-Han Zuo,Jia-Can Yan,Jiang-Yan Chen,Anantkumar J. Umbarkar
第一作者：范国峰
论文类型：期刊论文
通讯作者：洪维强
学科门类：工学
文献类型：J
卷号：145
期号：3
页面范围：3813-3837
ISSN号：1526-1492
是否译文：否
发表时间：2025-01-01
收录刊物：SCI