University Research
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1
Academic department
Department of Mathematics
Description
Extending classic finite frameworks to continuous settings, this paper proposes the concept of gamma belief functions and gamma fuzzy sets. It shows that both the combination of gamma belief functions and the intersection of gamma fuzzy sets remain within the gamma family, enabling their application in combining gamma probability judgments in decision making and gamma regression models in ensemble learning. Using both simulated and real datasets, and under both constant and varying dispersion assumptions, experimental results show that the combined gamma regression models closely approximate the reference models learned from the full datasets, aligning with the objectives of bootstrapping. Notably, when evaluated against ground truth, the combined models outperform both the individual component models and the reference models in predictive accuracy.
Publisher name
Elsevier
Grant Information
N/A
Data Management
N/A
Document Type
Article
Digital Object Identifier (DOI) Link
https://doi.org/10.1016/j.eswa.2026.131808
Publication Date
6-15-2026
Publication Title
Expert Systems with Applications
Volume
316
Recommended Citation
Liu, Liping, "Gamma Belief Functions and Fuzzy Sets and Application to Combining Predictive Models" (2026). University Research. 54.
https://ideaexchange.uakron.edu/university_research/54
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.