ISSN:
1013-9826
Source:
Scientific.Net: Materials Science & Technology / Trans Tech Publications Archiv 1984-2008
Topics:
Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
Notes:
A three-layer back-propagation neural network model based on the non-linear relationshipbetween the size of the SrTiO3 nanocrystalline and the technology factors, such as reaction time, reactiontemperature, raw material adding amount of NaOH and SrCl2, and the rate of TiCl4/Hl, was established.Moreover, in order to accelerate the converging rate and avoid the non-converging situation, themomentum terms are introduced. Besides, the variable learning speed is adopted. At the same time, theinput variables were pretreated by using the main component analysis firstly. And the results show that theimproved back-propagation neural network model is very efficient for predication of the SrTiO3nanocrystalline size
Type of Medium:
Electronic Resource
URL:
http://www.tib-hannover.de/fulltexts/2011/0528/01/54/transtech_doi~10.4028%252Fwww.scientific.net%252FKEM.336-338.2497.pdf
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