An Investigation of Alternative Methods for the Inference of Probabilistic-Fuzzy Systems

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17610%2F25%3AA2603BTF" target="_blank" >RIV/61988987:17610/25:A2603BTF - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/10.1007/978-3-032-00891-6_9" target="_blank" >https://link.springer.com/10.1007/978-3-032-00891-6_9</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-032-00891-6_9" target="_blank" >10.1007/978-3-032-00891-6_9</a>

Result language
angličtina
Original language name
An Investigation of Alternative Methods for the Inference of Probabilistic-Fuzzy Systems
Original language description
We focus on the inference process in a probabilistic-fuzzy IF-THEN rule system, where antecedents are modeled as fuzzy sets and consequents as weighted quantile functions, offering insights into the probability distribution of response data. While the weighted arithmetic mean has been the conventional inference method, other suitable approaches exist. This work compares it with three alternatives: the weighted geometric mean, weighted $L_1$ minimization, and a mixture distribution-based method. Through experiments on both simulated and real-world data, we evaluate their performance using standard statistical measures.
Czech name
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Czech description
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Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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