This article explores the current applications of artificial intelligence (AI) in chromatography. It anticipates AI’s ...

An ARIMA model can be understood by outlining each of its components as follows: Each component in ARIMA functions as a parameter with ... computer algorithms and machine learning techniques ...

Abstract: To address the problems of low classification accuracy, redundancy of feature subsets, and performance susceptibility to parameters ... improved Slime Mould Algorithm with multi-strategy was ...

They typically 1) use stochastic operators, making each run unique, and 2) often have algorithmic control parameters that have an unpredictable impact on convergence. Although both 1) and 2) affect ...

What are machine learning algorithms ... at the new parameter values. Eventually, with luck, the process converges. The variants on steepest descent try to improve the convergence properties.

These algorithms automatically adjust (learn) their internal parameters based on data. However, there is a subset of parameters that is not learned and that have to be configured by an expert.