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.

Regarding the Python code segment, the PLSR (Partial Least Squares Regression) modeling module is currently undergoing refinement. The research modeling has been conducted using The Unscrambler X 10.4 for the modeling aspect. The remainder of the code is operational. It features a GUI (Graphical User Interface) in Chinese, necessitating prior familiarity by the users