Biosensor response to multi-component mixtures statistical analysis and forecasting
Articles
Romas Baronas
Vilnius University
Sigitas Būda
Vilnius University
Feliksas Ivanauskas
Institute of Mathematics and Informatics
Pranas Vaitkus
Vilnius University
Published 2023-09-21
https://doi.org/10.15388/LMR.2006.30739
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Keywords

biosensor
modelling
neural networks

How to Cite

Baronas, R. (2023) “Biosensor response to multi-component mixtures statistical analysis and forecasting”, Lietuvos matematikos rinkinys, 46(spec.), pp. 338–344. doi:10.15388/LMR.2006.30739.

Abstract

This paper deals with an analysis of the electrochemical biosensors and their response to multi-component mixtures. The main task is to build a mathematical model for estimation the concentration of each mixture component from the biosensor response data. Two different types of biosensors: amperometric and potenciometric are analysed. Due to high dimensionality of biosensor output data the principal component analysis is applied. Additional multivariate analysis of variance is used to analyze the response sensitivity  of each biosensor type. Finally a concentration estimation model based on ensemble of neural networks is presented.

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