The prediction of the microstructure constituents of spheroidal graphite cast iron by using thermal analysis and artificial neural networks

Glavaš, Zoran and Unkić, Faruk and Lisjak, Dragutin (2010) The prediction of the microstructure constituents of spheroidal graphite cast iron by using thermal analysis and artificial neural networks. = The prediction of the microstructure constituents of spheroidal graphite cast iron by using thermal analysis and artificial neural networks. Archives of Metallurgy and Materials, 55 (1). pp. 247-253. ISSN 1733-3490. Vrsta rada: ["eprint_fieldopt_article_type_article" not defined]. Kvartili JCR: Q3 (2010). Točan broj autora: 3.

[img]
Preview
Text
The prediction of the microstructure constituents of spheroidal graphite cast iron by using thermal analysis and artificial neural networks.pdf - Published Version Jezik dokumenta:English

Download (2MB) | Preview
Official URL: http://imim.pl/files/archiwum/Vol1_2010/29.pdf

Abstract

This paper presents the application of articial neural networks in the production process of spheroidal graphite cast iron. Backpropagation neural networks have been established to predict the microstructure constituents (ferrite content, pearlite conent, nodule count and nodularity) of speroidal geaphite cast iron using the thermal analysis parameters as inputs. Generalization properties of the developed artificial neural netyworks are very good, which id=s confirmed by a very good accordance between the predicted and the targeted values of the microstructure constituents on a new data that was not included in the training data set.

Item Type: Article (["eprint_fieldopt_article_type_article" not defined])
Keywords (Croatian): Artificial neural networks; Microstructure constituents; Spheroidal graphite cast iron; Thermal analysis
Subjects: TECHNICAL SCIENCE
Divisions: 700 Department of Industrial Engineering > 720 Chair of Production Control
Indexed in Web of Science: Yes
Indexed in Current Contents: Yes
Citations JCR: 0 (08.02.2018.)
Quartiles: Q3 (2010)
Citations SCOPUS: 6 (08.02.2018.)
Date Deposited: 14 Apr 2015 09:20
Last Modified: 08 Feb 2018 13:39
URI: http://repozitorij.fsb.hr/id/eprint/3674

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year