Wyniki wyszukiwania - BazTech

Ograniczanie wyników

1 Management and Production Engineering Review

1 2019

Powiadomienia systemowe

Sesja wygasła!

Znaleziono wyników: 1

Liczba wyników na stronie

Wyniki wyszukiwania

Wyszukiwano:
w słowach kluczowych: k-nearest neighbours algorithm

Sortuj według:

Ogranicz wyniki do:

Application of instance-based learning for cast iron casting defects prediction

Sika Robert, Szajewski Damian, Hajkowski Jakub, Popielarski Paweł

Management and Production Engineering Review

2019

Vol. 10, No. 4

101--107

The paper presents an example of Instance-Based Learning using a supervised classiﬁcation method of predicting selected ductile cast iron castings defects. The test used the algorithm of k-nearest neighbours, which was implemented in the authors’ computer application. To ensure its proper work it is necessary to have historical data of casting parameter values registered during casting processes in a foundry (mould sand, pouring process, chemical composition) as well as the percentage share of defective castings (unrepairable casting defects). The result of an algorithm is a report with ﬁve most possible scenarios in terms of occurrence of a cast iron casting defects and their quantity and occurrence percentage in the casts series. During the algorithm testing, weights were adjusted for independent variables involved in the dependent variables learning process. The algorithms used to process numerous data sets should be characterized by high eﬃciency, which should be a priority when designing applications to be implemented in industry. As it turns out in the presented mathematical instance-based learning, the best quality of ﬁt occurs for speciﬁc values of accepted weights (set #5) for number k = 5 nearest neighbours and taking into account the search criterion according to “product index”.