Using Support Vector Regression to Predict the Overall Equipment Effectiveness Indicator-Reference-Cited by-同舟云学术

Using Support Vector Regression to Predict the Overall Equipment Effectiveness Indicator

Published:2022-05-18 Issue: Volume: Page:
ISSN:
Container-title:2022 International Conference on Intelligent Systems and Computer Vision (ISCV)
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Author:

Imane Mjimer¹,Aoula Es-Saadia¹,Achouyab El Hassan²

Affiliation:

1. Universite Hassan II Casablanca, Ecole Normale Superieure de l’Enseignement Technique,Laboratoire Signaux, Systèmes Distribués et Intelligence Artificielle,Mohammedia,Morocco

2. Universite Hassan II Casablanca, Faculte des Sciences et Techniques Mohammedia,Laboratory of Condensed Matter Physics and Renewable Energies,Mohammedia,Morocco

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9806043/9806057/09806111.pdf?arnumber=9806111

Reference23 articles.

1. Wave overtopping predictions using an advanced machine learning technique

2. A hybrid of Random Forest and Deep Auto-Encoder with support vector regression methods for accuracy improvement and uncertainty reduction of long-term streamflow prediction;abbasi;Journal of Hydrology,2020

3. Damage degree prediction method of CFRP structure based on fiber Bragg grating and epsilon-support vector regression

4. A Tutorial on Support Vector Regression;smola,1998

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1. Overall Equipment Effectiveness Prediction with Multiple Linear Regression for Semi-automatic Automotive Assembly Lines;Periodica Polytechnica Mechanical Engineering;2023-09-07

2. Cumulative and Rolling Horizon Prediction of Overall Equipment Effectiveness (OEE) with Machine Learning;Big Data and Cognitive Computing;2023-08-02