An artificial neural network approach and sensitivity analysis in predicting skeletal muscle forces
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21220%2F14%3A00217933" target="_blank" >RIV/68407700:21220/14:00217933 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.5277/abb140314" target="_blank" >http://dx.doi.org/10.5277/abb140314</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.5277/abb140314" target="_blank" >10.5277/abb140314</a>
Alternative languages
Result language
angličtina
Original language name
An artificial neural network approach and sensitivity analysis in predicting skeletal muscle forces
Original language description
This paper presents the use of an artificial neural network (NN) approach for predicting the muscle forces around the elbow joint. The main goal was to create an artificial NN which could predict the musculotendon forces for any general muscle without significant errors.
Czech name
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Czech description
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Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
JJ - Other materials
OECD FORD branch
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Result continuities
Project
<a href="/en/project/TA01010185" target="_blank" >TA01010185: New materials and coatings for joint replacement bionical design</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Acta of Bioengineering and Biomechanics
ISSN
1509-409X
e-ISSN
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Volume of the periodical
16
Issue of the periodical within the volume
3
Country of publishing house
PL - POLAND
Number of pages
9
Pages from-to
119-127
UT code for WoS article
000345162000014
EID of the result in the Scopus database
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