HPC的输入变量选择算法

D. Gradišar, M. Glavan
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引用次数: 1

摘要

本文讨论了整体生产控制(HPC)问题。HPC的主要思想是推导出一种优化策略,该策略基于只有几个生产关键性能指标(pKPI)的简单模型。HPC方法的主要挑战是推导适当的pKPI模型,其中主要步骤是:数据预处理,pKPI定义,输入变量选择(IVS)和黑盒建模。在本文中,我们关注的是选择最具影响力的输入的问题,其中回顾了不同的IVS方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Input variable selection algorithms for HPC
The paper refer to the problem of a holistic production control (HPC). The main idea of HPC is to derive an optimisation strategy which is based on a simple model of only a few production Key Performance Indicators (pKPI). The main challenge of the HPC approach is the derivation of an appropriate pKPI model, where the main steps are: data preprocessing, pKPI definition, input variables selection (IVS) and black-box modelling. In this paper we are focused on the problem of the selection of the most influential inputs, where the review of different IVS methods is given.
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