Quantitative analysis of spectral data based on stochastic configuration networks DOI
Lixin Zhang, Zhensheng Huang, Xiao Zhang

и другие.

Analytical Methods, Год журнала: 2024, Номер 16(28), С. 4794 - 4806

Опубликована: Янв. 1, 2024

In quantitative analysis of spectral data, traditional linear models have fewer parameters and faster computation speed.

Язык: Английский

Design and Study of Composite Film Preparation Platform DOI Creative Commons
Chao Li, Wenxin Li,

Guangqin Wu

и другие.

Crystals, Год журнала: 2024, Номер 14(5), С. 389 - 389

Опубликована: Апрель 23, 2024

This study aims to develop equipment for the preparation of composite films and successfully implement a film thickness prediction function. During research process, we segmented mechanical structure thin into distinct modules, completed structural design core module, validated stability process chamber, as well reasonableness strength stiffness through simulation. Additionally, devised regression model predicting films. The input features included sputtering air pressure, current, time magnetron samples, evaporation volume current vacuum samples. Simultaneously, output were both Subsequently, established designed conducted experimental verification. experiments, prepared Cr-Al utilized AFM surface morphology analysis. results confirmed excellent performance produced by equipment, demonstrating reliability equipment.

Язык: Английский

Процитировано

1

Quantitative analysis of spectral data based on stochastic configuration networks DOI
Lixin Zhang, Zhensheng Huang, Xiao Zhang

и другие.

Analytical Methods, Год журнала: 2024, Номер 16(28), С. 4794 - 4806

Опубликована: Янв. 1, 2024

In quantitative analysis of spectral data, traditional linear models have fewer parameters and faster computation speed.

Язык: Английский

Процитировано

0