Titlebook: Rough Sets and Current Trends in Computing; 9th International Co Chris Cornelis,Marzena Kryszkiewicz,Lin Shang Conference proceedings 2014

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書目名稱Rough Sets and Current Trends in Computing影響因子(影響力)




書目名稱Rough Sets and Current Trends in Computing影響因子(影響力)學(xué)科排名




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書目名稱Rough Sets and Current Trends in Computing被引頻次學(xué)科排名




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書目名稱Rough Sets and Current Trends in Computing讀者反饋學(xué)科排名

BABY

Improving the ,-Precision and OWA Based Fuzzy Rough Set Models: Definitions, Properties and Robustne adjust the .-precision and the ordered weighted average based fuzzy rough set models in such a way that the number of theoretical properties increases. Furthermore, we evaluate the robustness of the new models a-.-PREC and a-OWA to noisy data and compare them to a general implicator-conjunctor-base

搖曳的微光

沉積物

Some Fundamental Laws of Partial First-Order Logic Based on Set Approximationsost general problem is what happens if in the semantics of first-order logic one uses the approximations of sets as semantic values of predicate parameters instead of sets given by their total interpretation in order to determine the truth values of formulas? The authors show some unexpected propert

iodides

MOCK

拱墻

minimal

故意

小官

A Comparison of Two Versions of the MLEM2 Rule Induction Algorithm Extended to Probabilistic Approxiprobabilistic approximations were additionally generalized to an arbitrary binary relation so that probabilistic approximations may be applied for incomplete data. We discuss two ways to induce rules from incomplete data using probabilistic approximations, by applying true MLEM2 algorithm and an emu