Cargando…
Using the Stochastic Gradient Descent Optimization Algorithm on Estimating of Reactivity Ratios
This paper describes an improved method of calculating reactivity ratios by applying the neuronal networks optimization algorithm, named gradient descent. The presented method is integral and has been compared to the following existing methods: Fineman–Ross, Tidwell–Mortimer, Kelen–Tüdös, extended K...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8400145/ https://www.ncbi.nlm.nih.gov/pubmed/34443284 http://dx.doi.org/10.3390/ma14164764 |
_version_ | 1783745245559652352 |
---|---|
author | Fazakas-Anca, Iosif Sorin Modrea, Arina Vlase, Sorin |
author_facet | Fazakas-Anca, Iosif Sorin Modrea, Arina Vlase, Sorin |
author_sort | Fazakas-Anca, Iosif Sorin |
collection | PubMed |
description | This paper describes an improved method of calculating reactivity ratios by applying the neuronal networks optimization algorithm, named gradient descent. The presented method is integral and has been compared to the following existing methods: Fineman–Ross, Tidwell–Mortimer, Kelen–Tüdös, extended Kelen–Tüdös and Error in Variable Methods. A comparison of the reactivity ratios that obtained different levels of conversions was made based on the Fisher criterion. The new calculation method for reactivity ratios shows better results than these other methods. |
format | Online Article Text |
id | pubmed-8400145 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-84001452021-08-29 Using the Stochastic Gradient Descent Optimization Algorithm on Estimating of Reactivity Ratios Fazakas-Anca, Iosif Sorin Modrea, Arina Vlase, Sorin Materials (Basel) Article This paper describes an improved method of calculating reactivity ratios by applying the neuronal networks optimization algorithm, named gradient descent. The presented method is integral and has been compared to the following existing methods: Fineman–Ross, Tidwell–Mortimer, Kelen–Tüdös, extended Kelen–Tüdös and Error in Variable Methods. A comparison of the reactivity ratios that obtained different levels of conversions was made based on the Fisher criterion. The new calculation method for reactivity ratios shows better results than these other methods. MDPI 2021-08-23 /pmc/articles/PMC8400145/ /pubmed/34443284 http://dx.doi.org/10.3390/ma14164764 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Fazakas-Anca, Iosif Sorin Modrea, Arina Vlase, Sorin Using the Stochastic Gradient Descent Optimization Algorithm on Estimating of Reactivity Ratios |
title | Using the Stochastic Gradient Descent Optimization Algorithm on Estimating of Reactivity Ratios |
title_full | Using the Stochastic Gradient Descent Optimization Algorithm on Estimating of Reactivity Ratios |
title_fullStr | Using the Stochastic Gradient Descent Optimization Algorithm on Estimating of Reactivity Ratios |
title_full_unstemmed | Using the Stochastic Gradient Descent Optimization Algorithm on Estimating of Reactivity Ratios |
title_short | Using the Stochastic Gradient Descent Optimization Algorithm on Estimating of Reactivity Ratios |
title_sort | using the stochastic gradient descent optimization algorithm on estimating of reactivity ratios |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8400145/ https://www.ncbi.nlm.nih.gov/pubmed/34443284 http://dx.doi.org/10.3390/ma14164764 |
work_keys_str_mv | AT fazakasancaiosifsorin usingthestochasticgradientdescentoptimizationalgorithmonestimatingofreactivityratios AT modreaarina usingthestochasticgradientdescentoptimizationalgorithmonestimatingofreactivityratios AT vlasesorin usingthestochasticgradientdescentoptimizationalgorithmonestimatingofreactivityratios |