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Heuristics-based modelling of human decision process | ||
| Iranian Journal of Fuzzy Systems | ||
| دوره 20، شماره 3، مرداد و شهریور 2023، صفحه 19-30 اصل مقاله (820.85 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22111/ijfs.2023.7636 | ||
| نویسندگان | ||
| M. Aggarwal* 1، 2؛ A. F. Tehrani3 | ||
| 1School of Artificial Intelligence and Data Science, IIT Jodhpur, Jodhpur, India | ||
| 2Digital Humanities, IIT Jodhpur, Jodhpur, India | ||
| 3Hof University of Applied Sciences, Hof, Germany | ||
| چکیده | ||
| Attitudinal Choquet integral (ACI) is a recent aggregation operator that considers in the aggregation process the criteria interaction and the DM's attitude, both of which are specific to the decision-maker. However, this capability comes at the cost of increased complexity that hinders its applicability in big data analytics. To address the same, in this paper, we explore some heuristics-based forms of the ACI operator, so as to somehow overcome its complexity. We devise new and efficient forms of $\mathcal{ACI}$, and test their validity in the real world datasets, against the backdrop of preference learning. | ||
| کلیدواژه‌ها | ||
| Attitudinal Choquet integral؛ efficiency؛ complexity reduction؛ attitudinal character؛ multi criteria decision making | ||
| مراجع | ||
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آمار تعداد مشاهده مقاله: 47 تعداد دریافت فایل اصل مقاله: 111 |
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