Future Graduate Salaries Prediction Model Based On Recurrent Neural Network

• Autorzy: Siłka Jakub , Wieczorek Michał , Woźniak Marcin

Identyfikatory

DOI

10.15439/2020F52

• Konferencja: Federated Conference on Computer Science and Information Systems (15 ; 06-09.09.2020 ; Sofia, Bulgaria)
• Języki publikacji: EN

Abstrakty

EN

Prediction models are widely applied in several fields. In this study we present a discussion on using Recurrent Neural Network as predictor for salaries of future graduates. The model is based on feature analysis which leads to input values of the predictor. We have analyzed several compositions and ideas. As a result we have selected Recurrent Neural Network to be the most accurate. Presented results confirm this selection and show high precision.

Słowa kluczowe

EN

recurrent neural network; RNN; prediction model

PL

rekurencyjne sieci neuronowe; RNN; model predykcyjny

• Wydawca: Polskie Towarzystwo Informatyczne
• Czasopismo: Annals of Computer Science and Information Systems
• Rocznik: 2020
• Tom: Vol. 21
• Strony: 427--430
• Opis fizyczny: Bibliogr. 16 poz., wz., wykr., rys.

Twórcy

autor

Siłka Jakub

• Faculty of Applied Mathematics, Silesian University of Technology, Kaszubska 23, 44-100 Gliwice, POLAND

autor

Wieczorek Michał

• Faculty of Applied Mathematics, Silesian University of Technology, Kaszubska 23, 44-100 Gliwice, POLAND

autor

Woźniak Marcin

• Faculty of Applied Mathematics, Silesian University of Technology, Kaszubska 23, 44-100 Gliwice, POLAND

Bibliografia

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Uwagi

1. Track 2: Computer Science & Systems

2. Technical Session: Advances in Computer Science & Systems

3. Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).