Abstract

Machine learning models are powerful and valuable tools for predicting results for any problems represented by multiple variables based on information contained in historical data. Predictive models have significant development potential in autonomous decision support systems based on collected and processed data and expert knowledge to effectively support decision-makers. This paper presents the application of an artificial neural network model called Multi-layer Perceptron (MLP) regressor to predict rankings based on MCDA evaluations performed earlier with expert participation. The results predicted by the model trained on training data demonstrate high consistency with the real ranking, confirming the high potential of this model in building autonomous decision support systems. The proposed approach was applied to predict European countries’ ranking regarding environmentally friendly, efficient, and affordable energy.

Recommended Citation

Watróbski, J., Baczkiewicz, A., & Rudawska, I. (2022). Multi-Layer Perceptron Regressor for Ranking Prediction in Information Systems for Sustainability Assessment. In R. A. Buchmann, G. C. Silaghi, D. Bufnea, V. Niculescu, G. Czibula, C. Barry, M. Lang, H. Linger, & C. Schneider (Eds.), Information Systems Development: Artificial Intelligence for Information Systems Development and Operations (ISD2022 Proceedings). Cluj-Napoca, Romania: Risoprint. ISBN: 978-973-53-2917-4. https://doi.org/10.62036/ISD.2022.29

Paper Type

Short Paper

DOI

10.62036/ISD.2022.29

Share

COinS
 

Multi-Layer Perceptron Regressor for Ranking Prediction in Information Systems for Sustainability Assessment

Machine learning models are powerful and valuable tools for predicting results for any problems represented by multiple variables based on information contained in historical data. Predictive models have significant development potential in autonomous decision support systems based on collected and processed data and expert knowledge to effectively support decision-makers. This paper presents the application of an artificial neural network model called Multi-layer Perceptron (MLP) regressor to predict rankings based on MCDA evaluations performed earlier with expert participation. The results predicted by the model trained on training data demonstrate high consistency with the real ranking, confirming the high potential of this model in building autonomous decision support systems. The proposed approach was applied to predict European countries’ ranking regarding environmentally friendly, efficient, and affordable energy.