Towards the modeling of atomic and molecular clusters energy by support vector regression
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F13%3A86088020" target="_blank" >RIV/61989100:27740/13:86088020 - isvavai.cz</a>
Alternative codes found
RIV/61989100:27240/13:86088020
Result on the web
<a href="http://dx.doi.org/10.1109/INCoS.2013.26" target="_blank" >http://dx.doi.org/10.1109/INCoS.2013.26</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/INCoS.2013.26" target="_blank" >10.1109/INCoS.2013.26</a>
Alternative languages
Result language
angličtina
Original language name
Towards the modeling of atomic and molecular clusters energy by support vector regression
Original language description
Simulations of molecular dynamics play an important role in computational chemistry and physics. Such simulations require accurate information about the state and properties of interacting systems. The computation of water cluster potential energy surface is a complex and computationally expensive operation. Therefore, machine learning methods such as Artificial Neural Networks have been recently employed to machine-learn and further approximate clusters potential energy surfaces. This works presents the application of another highly successful machine learning method, the Support Vector Regression, for the modeling and approximation of the potential energy of water clusters as representatives of more general molecular clusters.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2013
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 - 5th International Conference on Intelligent Networking and Collaborative Systems, INCoS 2013
ISBN
978-0-7695-4988-0
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
121-126
Publisher name
IEEE
Place of publication
Danvers
Event location
Xi'an
Event date
Sep 9, 2013
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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