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Disambiguation of "Kosheleva, Olga"

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Which Activation Function Works Best for Training Artificial Pancreas: Empirical Fact and Its Theoretical Explanation.

, , , , , and . SSCI, page 496-500. IEEE, (2023)

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To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

Üstün Olgay

Olga Munteanu

Rapidly changing automotive global value chains in Hungary: multinational vs. local firm perspectives. Uni Leipzig, (2009)

Olga Bruskina

Periinterventionelle Blutungskomplikationen und die Auswirkung auf den 1-Jahresverlauf nach perkutaner Koronarintervention: Blutungen als zusätzliche Komponente eines kombinierten klinischen Endpunktes. TU München, (2008)

Olga Osetska

Homo- and heterodinuclear luminescent helicates. TU Aachen, (2008)

Olga Sosnovtseva

 

Other publications of authors with the same name

Intelligence techniques are needed to further enhance the advantage of groups with diversity in problem solving., , , , and . HIMA, page 48-55. IEEE, (2009)Uncertain information fusion and knowledge integration: How to take reliability into account., , , and . IFSA-SCIS, page 1-8. IEEE, (2017)Which material design is possible under additive manufacturing: A fuzzy approach., , and . IFSA-SCIS, page 1-5. IEEE, (2017)Between Dog and Wolf: A Continuous Transition from Fuzzy to Probabilistic Estimates., , , and . FUZZ-IEEE, page 1-5. IEEE, (2019)Why polynomial formulas in soft computing, decision making, etc.?, and . FUZZ-IEEE, page 1-5. IEEE, (2010)Unimodality, Independence Lead to NP-Hardness of Interval Probability Problems., , , and . Reliab. Comput., 13 (3): 261-282 (2007)How to Predict Nesting Sites and How to Measure Shoreline Erosion: Fuzzy and Probabilistic Techniques for Environment-Related Spatial Data Processing., , , and . WCSC, volume 361 of Studies in Fuzziness and Soft Computing, page 595-604. Springer, (2016)Simple linear interpolation explains all usual choices in fuzzy techniques: Membership functions, t-norms, t-conorms, and defuzzification., , , , , and . NAFIPS/WConSC, page 1-5. IEEE, (2015)Quantum Econometrics: How to Explain Its Quantitative Successes and How the Resulting Formulas Are Related to Scale Invariance, Entropy, and Fuzziness., , , and . IUKM, volume 10758 of Lecture Notes in Computer Science, page 264-275. Springer, (2018)Why Triangular Membership Functions Are Successfully Used in F-Transform Applications: A Global Explanation to Supplement the Existing Local Ones., , and . Axioms, 8 (3): 95 (2019)