Support Vector Machines for Control of Multimodal Processes
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F22%3A00354007" target="_blank" >RIV/68407700:21730/22:00354007 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-030-96302-6_35" target="_blank" >http://dx.doi.org/10.1007/978-3-030-96302-6_35</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-96302-6_35" target="_blank" >10.1007/978-3-030-96302-6_35</a>
Alternative languages
Result language
angličtina
Original language name
Support Vector Machines for Control of Multimodal Processes
Original language description
In recent manufacturing processes, the number of common causes of variation increases with the complexity of processes, leading to different shifts of the in-control process between multiple modes. Such a multimodal process violates the normality assumption, which decreases the efficiency of the commonly used methods and often disables the usage of SPC. This paper investigates the performance of one-class support vector machine (OSVM) in a multimodal setting. We have generated 5-modal synthetic data set with two correlated variables that violate the normality assumption. These methods were compared on the horizontally, vertically, and diagonally shifted out-of-control data. We have found that OSVM outperforms the other two commonly used SPC methods, which demonstrates that its more flexible decision boundary can naturally wrap the data from multimodal processes and can bring benefits to the control of modern complex processes.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 13th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2021)
ISBN
978-3-030-96302-6
ISSN
2367-3370
e-ISSN
2367-3389
Number of pages
10
Pages from-to
384-393
Publisher name
Springer
Place of publication
Cham
Event location
online
Event date
Dec 15, 2021
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000774224200035