This article proposes a new genetic algorithm (GA) methodology to obtain parsimonious
support vector regression (SVR) models capable of predicting highly precise setpoints in a …

This study developed 12 prediction models using two types of data matrix (daily means and
a selection of the mean for the first 6h of the day). The Persistence parametric prediction …

This study concerns with the control of basic oxygen furnace (BOF) steelmaking process and
proposes a dynamic control model based on adaptive-network-based fuzzy inference …

A new, comprehensive mathematical model of continuous annealing furnaces is developed,
under consideration of both the radiative and convective heat transfer of the furnace …

The increasing demand for specialized steel products necessitates precise temperature
control in annealing furnaces. Conventional nonlinear physical predictive models are often …

Temperature in a continuous annealing furnace is studied by furnace modelling using two
methods. A 3D model is used to investigate the temperature distribution of the steel strip that …

This paper presents an experience based on the use of association rules from multiple time
series captured from industrial processes. The main goal is to seek useful knowledge for …

The current study shows how data mining and artificial intelligence techniques can be used
to introduce improvements in the rubber extrusion production process. One of the keys for …

In the industrial arena, artificial neural networks are among the most significant techniques
in system modelling because of their efficiency and simplicity. In this paper, we present an …

Advanced statistical models can help industry to design more economical and rational
investment plans. Fault detection and diagnosis is an important problem in continuous hot …