All

What are you looking for?

All
Projects
Results
Organizations

Quick search

  • Projects supported by TA ČR
  • Excellent projects
  • Projects with the highest public support
  • Current projects

Smart search

  • That is how I find a specific +word
  • That is how I leave the -word out of the results
  • “That is how I can find the whole phrase”

Ensemble of heterogeneous flexible neural tree for the approximation and feature-selection of Poly (lactic-co-glycolic acid) micro- and nanoparticle

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F16%3A86095758" target="_blank" >RIV/61989100:27240/16:86095758 - isvavai.cz</a>

  • Alternative codes found

    RIV/61989100:27740/16:86095758

  • Result on the web

    <a href="http://link.springer.com/chapter/10.1007/978-3-319-29504-6_16" target="_blank" >http://link.springer.com/chapter/10.1007/978-3-319-29504-6_16</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-319-29504-6_16" target="_blank" >10.1007/978-3-319-29504-6_16</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Ensemble of heterogeneous flexible neural tree for the approximation and feature-selection of Poly (lactic-co-glycolic acid) micro- and nanoparticle

  • Original language description

    In this work, we used an adaptive feature-selection and function approximation model, called, flexible neural tree (FNT) for predicting Poly (lactic-co-glycolic acid) (PLGA) micro- and nanoparticle's dissolution-rates that bears significant role in the pharmaceutical, medical, and drug manufacturing industries. Several factor influences PLGA nanoparticles dissolution-rate prediction. FNT model enable us to deal with feature-selection and prediction simultaneously. However, a single FNT model may or may not offer a generalized solution. Hence, to build a generalized model, we used an ensemble of FNTs. In this work, we have provided a comprehensive study for examining the most significant (influencing) features that influences dissolution rate prediction.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    R - Projekt Ramcoveho programu EK

Others

  • Publication year

    2016

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Advances in Intelligent Systems and Computing. Volume 427

  • ISBN

    978-3-319-29503-9

  • ISSN

    2194-5357

  • e-ISSN

  • Number of pages

    11

  • Pages from-to

    155-165

  • Publisher name

    Springer Verlag

  • Place of publication

    London

  • Event location

    Paříž

  • Event date

    Sep 9, 2015

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000371912400016