Predictive Power of Fuzzy Model vs. Statistical Model: Prediction of Tesla Car Sales
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F75081431%3A_____%2F25%3A00002926" target="_blank" >RIV/75081431:_____/25:00002926 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/article/10.1007/s10614-025-11123-8" target="_blank" >https://link.springer.com/article/10.1007/s10614-025-11123-8</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Predictive Power of Fuzzy Model vs. Statistical Model: Prediction of Tesla Car Sales
Original language description
The authors present two distinct approaches for forecasting time series of complex systems characterized by non-stationarity and uncertainty. The first approach is a fuzzy logic-based method, which incorporates expert opinion to define the system using membership functions and fuzzy decision rules. This approach facilitates the development of knowledge applications capable of processing ambiguity and inaccuracy.
Czech name
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Czech description
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Classification
Type
J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database
CEP classification
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OECD FORD branch
50200 - Economics and Business
Result continuities
Project
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Continuities
V - Vyzkumna aktivita podporovana z jinych verejnych zdroju
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Computational Economics
ISSN
0927-7099
e-ISSN
1572-9974
Volume of the periodical
Neuveden
Issue of the periodical within the volume
2025
Country of publishing house
NL - THE KINGDOM OF THE NETHERLANDS
Number of pages
30
Pages from-to
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UT code for WoS article
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EID of the result in the Scopus database
2-s2.0-105019591070