Feasible Robustness in Adaptive Monitoring of Complex Harmonic Time Series Using In-Parameter-Linear Nonlinear Neural Architectures

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21220%2F25%3A00384196" target="_blank" >RIV/68407700:21220/25:00384196 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.1016/j.procs.2025.01.287" target="_blank" >https://doi.org/10.1016/j.procs.2025.01.287</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.procs.2025.01.287" target="_blank" >10.1016/j.procs.2025.01.287</a>

Result language

angličtina

Original language name

Feasible Robustness in Adaptive Monitoring of Complex Harmonic Time Series Using In-Parameter-Linear Nonlinear Neural Architectures

Original language description

This work studies the meta-parameter influence on adaptive prediction of complex harmonic signals such as ball bearing vibrations and its monitoring via neural weights using in-parameter-linear nonlinear neural architecture (IPLNA). We show that Higher-Order Neural Units (HONUs) also with higher nonlinearity orders have the potential to approximate and thus monitor complex behaviour of systems with inherent linearity (such as ball bearing vibrations) without overfitting during real-time learning. We show that the presence of multicollinearities in the input state does not necessarily reduce the generalizing properties of HONU models and that the increased nonlinearity of HONUs does not necessarily introduce an overfitting problem. Therefore, due to the analogy of the mathematical architecture of HONUs to time-variant linear dynamical systems and their underlying mathematical-physical understanding, we present a basis for novel research of explainable machine learning methods for predictive maintenance.

Czech name

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Czech description

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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)

Project

<a href="/en/project/TN02000010" target="_blank" >TN02000010: National Competence Centre of Mechatronics and Smart Technologies for Mechanical Engineering</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2025

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Procedia Computer Science

ISBN

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ISSN

1877-0509

e-ISSN

1877-0509

Number of pages

10

Pages from-to

2268-2277

Publisher name

Elsevier B.V.

Place of publication

Amsterdam

Event location

Praha

Event date

Nov 20, 2024

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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