Application of artificial neural network and genetic algorithm to healthcarewaste prediction

• Autorzy: Arabgol S. , Ko H. S.

Identyfikatory

DOI

10.2478/jaiscr-2014-0017

• Języki publikacji: EN

Abstrakty

EN

Prompt and proper management of healthcare waste is critical to minimize the negative impact on the environment. Improving the prediction accuracy of the healthcare waste generated in hospitals is essential and advantageous in effective waste management. This study aims at developing a model to predict the amount of healthcare waste. For this purpose, three models based on artificial neural network (ANN), multiple linear regression (MLR), and combination of ANN and genetic algorithm (ANN-GA) are applied to predict the waste of 50 hospitals in Iran. In order to improve the performance of ANN for prediction, GA is applied to find the optimal initial weights in the ANN. The performance of the three models is evaluated by mean squared errors. The obtained results have shown that GA has significant impact on optimizing initial weights and improving the performance of ANN.

Słowa kluczowe

EN

artificial neural network; ANN; application; hospital; genetic algorithm; GA; healthcare waste

• Wydawca: University of Social Sciences
• Czasopismo: Journal of Artificial Intelligence and Soft Computing Research
• Rocznik: 2013
• Tom: Vol. 3, No. 4
• Strony: 243--250
• Opis fizyczny: Bibliogr. 22 poz., rys.

Twórcy

autor

Arabgol S.

• Department of Mechanical and Industrial Engineering, Southern Illinois University Edwardsville, Edwardsville, IL 62026-1805, USA

autor

Ko H. S.

• Department of Mechanical and Industrial Engineering, Southern Illinois University Edwardsville, Edwardsville, IL 62026-1805, USA

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