Szczegóły publikacji
Opis bibliograficzny
Artificial neural networks as a tool for supporting a moulding sand control system based on the dependency between selected moulding sand properties / Barbara MRZYGŁÓD, Jarosław JAKUBSKI, Andrzej OPALIŃSKI, Krzysztof REGULSKI // Journal of Casting & Materials Engineering [Dokument elektroniczny]. — Czasopismo elektroniczne ; ISSN 2543-9901. — 2023 — vol. 7 no. 2, s. 15–21. — Wymagania systemowe: Adobe Reader. — Bibliogr. s. 20–21, Abstr. — Publikacja dostępna online od: 2023-05-22
Autorzy (4)
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 147963 |
|---|---|
| Data dodania do BaDAP | 2023-08-08 |
| Tekst źródłowy | URL |
| DOI | 10.7494/jcme.2023.7.2.15 |
| Rok publikacji | 2023 |
| Typ publikacji | artykuł w czasopiśmie |
| Otwarty dostęp |  |
| Creative Commons | |
| Czasopismo/seria | Journal of Casting & Materials Engineering |
Abstract
The article presents the potential for using artificial neural networks to support decisions related to the rebonding of green mould-ing sand. The basic properties of the moulding sand tested in foundries are discussed, especially compactibility as it gives the most information about the quality of green moulding sand. First, the data that can predict the compactibility value without the need for testing are defined. Next, a method for constructing an artificial neural network is presented and the network model which pro-duced the best results is analysed. Additionally, two applications were designed to allow the investigation results to be searchable by determining the range of values of the moulding sand parameters.
