A Model for Inversion of Hyperspectral Characteristics of Phosphate Content in Mural Plaster Based on Fractional-Order Differential Algorithm

This compendium encompasses the entirety of hyperspectral data acquired across a spectrum of experimental scenarios (initially delineating the wavelength in the foremost column, followed by a sequential arrangement of every 10 columns demarcating a unique set of data under a specific condition, cumulatively spanning 51 columns), accompanied by an Excel spreadsheet detailing the electrical conductivity measurements of all mural plaster specimens. Within this hyperspectral data repository, each column, save for the one designating the wavelength, is meticulously aligned in a one-to-one correspondence with each column of the Excel spreadsheet, thereby encapsulating both the hyperspectral and electrical conductivity data for the respective mural plaster samples.Scholars can utilize this dataset to replicate the hyperspectral feature inversion model for phosphate content in mural plaster. Before modeling, it is customary to eliminate 10% of the data identified as outliers.

本汇编涵盖了在一系列实验场景中获取的整个高光谱数据集（最初在第一列中界定波长，随后每10列依次划分特定条件下的独立数据集，总计51列），并附有详述所有壁画抹灰试样电导率测量的Excel电子表格。在高光谱数据库中，除波长标识列外，每一列均与Excel电子表格的每一列进行精确的一对一对应，从而包含了相应壁画抹灰样本的高光谱和电导率数据。学者们可以利用此数据集复制壁画抹灰中磷酸含量的高光谱特征反演模型。在建模之前，通常需移除识别出的10%异常数据。