Forecasting Models of Tool use in Different Intervals of Time

• Autorzy: Izabela Rojek
• Języki publikacji: EN

Abstrakty

EN

In the paper the forecasting models of tool use in different intervals of time were presented. The models were worked out by the use of hybrid neural networks in the form of: linear neural network (L) - multi-layer networks with error backpropagation (MLP), L network - Radial Basis Function network (RBF), MLP network - RBF network and L network - MLP network - RBF network. The comparison of these models was executed. The effectiveness of forecasting of tool use in different time intervals is the measure of model evaluation. These models are used at the design stage of manufacturing process with the aim to plan production and prevent standstill due to lack of tools, and special tools in particular. The created models were tested on real data from an enterprise. (original abstract)

Słowa kluczowe

EN

Forecasting; Evaluation model; Neural networks

PL

Prognozowanie; Model rozwoju; Sieci neuronowe

• Czasopismo: Management and Production Engineering Review
• Rocznik: 2010
• Tom: 1
• Numer: nr 1
• Strony: 31--39

Twórcy

autor

Izabela Rojek

• Kazimierz Wielki University in Bydgoszcz, Poland

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