Accurate prediction of hyaluronic acid concentration under temperature perturbations using near-infrared spectroscopy and deep learning

• Published in: Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Vol. 317; p. 124396
• Main Authors: Tian, Weilu, Zang, Lixuan, Ijaz, Muhammad, Dong, Zaixing, Zhang, Shudi, Gao, Lele, Li, Meiqi, Nie, Lei, Zang, Hengchang
• Format: Journal Article
• Language: English
• Published: England Elsevier B.V 05.09.2024
• Subjects: Aquaphotomics; Deep extreme learning machine; Feature fusion; Near-infrared spectroscopy; Walrus optimization algorithm; Feature fusion; Aquaphotomics; Walrus optimization algorithm; Deep extreme learning machine; Near-infrared spectroscopy
• ISSN: 1386-1425; 1873-3557
• DOI: 10.1016/j.saa.2024.124396

[Display omitted] •A novel feature fusion method based on an intersection strategy has been proposed.•An innovative, multi-strategy improved Walrus Optimization Algorithm (MIWaOA) has been created.•A new deep extreme learning machine (MIWaOA-DELM) has been constructed. 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.