Extracting Valuable Information from Big Data for Machine Learning Control: An Application for a Gas Lift Process

Machine learning: Overview of the recent progresses and implications for the process systems engineering field

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The impact of digitalization on the future of control and operations

(2018) Alf J. Isaksson et al.   COMPUTERS & CHEMICAL ENGINEERING

Echo State Networks for data-driven downhole pressure estimation in gas-lift oil wells

(2017) Eric A. Antonelo et al.   NEURAL NETWORKS

A soft sensor for industrial melt index prediction based on evolutionary extreme learning machine

(2016) Miao Zhang et al.   CHINESE JOURNAL OF CHEMICAL ENGINEERING

Robust learning algorithm for multiplicative neuron model artificial neural networks

(2016) Eren Bas et al.   EXPERT SYSTEMS WITH APPLICATIONS

Echo state network based predictive control with particle swarm optimization for pneumatic muscle actuator

(2016) Jian Huang et al.   JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS

Data-Based Techniques Focused on Modern Industry: An Overview

(2015) Shen Yin et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Geological mapping using remote sensing data: A comparison of five machine learning algorithms, their response to variations in the spatial distribution of training data and the use of explicit spatial information

(2013) Matthew J. Cracknell et al.   COMPUTERS & GEOSCIENCES

Dual composition control and soft estimation for a pilot distillation column using a neurogenetic design

(2012) J. Fernandez de Canete et al.   COMPUTERS & CHEMICAL ENGINEERING

From model-based control to data-driven control: Survey, classification and perspective

(2012) Zhong-Sheng Hou et al.   INFORMATION SCIENCES

On Instability in Gas Lift Wells and Schemes for Stabilization by Automatic Control

(2008) Gisle O. Eikrem et al.   SPE Production & Operations

Nonlinear parameter estimation through particle swarm optimization

(2007) Marcio Schwaab et al.   CHEMICAL ENGINEERING SCIENCE