透明质酸
红外线的
光谱学
红外光谱学
功能近红外光谱
材料科学
生物医学工程
化学
光学
物理
医学
神经科学
生物
解剖
有机化学
认知
量子力学
前额叶皮质
作者
Weilu Tian,Lixuan Zang,Muhammad Ijaz,Dong Zeng,S. S. Zhang,Lele Gao,Meiqi Li,Lei Nie,Hengchang Zang
标识
DOI:10.1016/j.saa.2024.124396
摘要
Accurate prediction of the concentration of a large number of hyaluronic acid (HA) samples under temperature perturbations can facilitate the rapid determination of HA's appropriate applications. Near-infrared (NIR) spectroscopy analysis combined with deep learning presents an effective solution to this challenge, with current research in this area being scarce. Initially, we introduced a novel feature fusion method based on an intersection strategy and used two-dimensional correlation spectroscopy (2DCOS) and Aquaphotomics to interpret the interaction information in HA solutions reflected by the fused features. Subsequently, we created an innovative, multi-strategy improved Walrus Optimization Algorithm (MIWaOA) for parameter optimization of the deep extreme learning machine (DELM). The final constructed MIWaOA-DELM model demonstrated superior performance compared to partial least squares (PLS), extreme learning machine (ELM), DELM, and WaOA-DELM models. The results of this study can provide a reference for the quantitative analysis of biomacromolecules in complex systems.
科研通智能强力驱动
Strongly Powered by AbleSci AI