Using robust generalized fuzzy modeling and enhanced symbolic regression to model tribological systems
Summary
Using robust generalized fuzzy modeling and enhanced symbolic regression to model tribological systems is a scholarly article[1].
Key Facts
Using robust generalized fuzzy modeling and enhanced symbolic regression to model tribological systems's instance of is recorded as scholarly article[2].
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APA4ort.xyz Knowledge Graph. (2026). Using robust generalized fuzzy modeling and enhanced symbolic regression to model tribological systems. Retrieved May 24, 2026, from https://4ort.xyz/entity/using-robust-generalized-fuzzy-modeling-and-enhanced-symbolic-regression-to-model-tribological-systems
MLA“Using robust generalized fuzzy modeling and enhanced symbolic regression to model tribological systems.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/using-robust-generalized-fuzzy-modeling-and-enhanced-symbolic-regression-to-model-tribological-systems.
BibTeX@misc{4ortxyz_using-robust-generalized-fuzzy-modeling-and-enhanced-symbolic-regression-to-model-tribological-systems_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Using robust generalized fuzzy modeling and enhanced symbolic regression to model tribological systems}}, year = {2026}, url = {https://4ort.xyz/entity/using-robust-generalized-fuzzy-modeling-and-enhanced-symbolic-regression-to-model-tribological-systems}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Using robust generalized fuzzy modeling and enhanced symbolic regression to model tribological systems — https://4ort.xyz/entity/using-robust-generalized-fuzzy-modeling-and-enhanced-symbolic-regression-to-model-tribological-systems (retrieved 2026-05-24)
