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Erschienen in: Neural Computing and Applications 10/2019

27.04.2018 | Original Article

Predictive mathematical model for solving multi-criteria decision-making problems

verfasst von: N. Deepa, K. Ganesan, Balaji Sethuramasamyraja

Erschienen in: Neural Computing and Applications | Ausgabe 10/2019

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Abstract

In this paper, a predictive mathematical model is proposed to identify the best alternatives from the given set of alternatives characterized by multiple criteria. An objective function is developed to find the ranking index of the alternatives. A new Comprehensive-Technique for Order Preference by Similarity to Ideal Solution (C-TOPSIS) method is proposed which combines the comprehensive weights of the criteria with TOPSIS method. The proposed predictive mathematical model generates a ranking of the alternatives. An experimental study has been carried out by taking agricultural data set of rice paddy crop to demonstrate and validate the developed model. The results show significant correlation between the ranks obtained by the proposed model and the ranks obtained from the average yield per hectare. Also the results of the proposed method outperform the results of the other ranking methods, namely VIKOR and ELECTRE, particularly in the real world example. Thus, the developed predictive mathematical model seems to provide better results for the given alternatives and can also be used for other decision-making problems.

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Metadaten
Titel
Predictive mathematical model for solving multi-criteria decision-making problems
verfasst von
N. Deepa
K. Ganesan
Balaji Sethuramasamyraja
Publikationsdatum
27.04.2018
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 10/2019
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-018-3505-2

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