Z
Zaoli Yang
Researcher at Beijing University of Technology
Publications - 50
Citations - 993
Zaoli Yang is an academic researcher from Beijing University of Technology. The author has contributed to research in topics: Fuzzy logic & Computer science. The author has an hindex of 12, co-authored 33 publications receiving 351 citations. Previous affiliations of Zaoli Yang include Harbin Engineering University.
Papers
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The ensemble deep learning model for novel COVID-19 on CT images.
TL;DR: An ensemble deep learning model can better meet the rapid detection requirements of the novel coronavirus disease COVID-19 and was compared with three component classifiers to evaluate accuracy, sensitivity, specificity, F value, and Matthews correlation coefficient.
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Robust multi-objective optimal design of islanded hybrid system with renewable and diesel sources/stationary and mobile energy storage systems
Zaoli Yang,Mojtaba Ghadamyari,Hossein Khorramdel,S.M. Alizadeh,Sasan Pirouzi,Muhammed Milani,Farzad Banihashemi,Noradin Ghadimi +7 more
TL;DR: Capacity of the method in extracting a robust IHS for sources and ESSs are validated depending on optimal economic and environmental conditions, and the scheme obtains a robust structure for the IHS.
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Decision Support Algorithm for Selecting an Antivirus Mask over COVID-19 Pandemic under Spherical Normal Fuzzy Environment.
TL;DR: A decision support algorithm based on the novel concept of the spherical normal fuzzy (SpNoF) set to maximize the utility of the antivirus mask is proposed and a multi-criteria decision-making method is established,based on the proposed operators, with SpNoF information.
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A decision-making algorithm for online shopping using deep-learning–based opinion pairs mining and q-rung orthopair fuzzy interaction Heronian mean operators
TL;DR: An online shopping support model using deep‐learning–based opinion mining and q‐rung orthopair fuzzy interaction weighted Heronian mean (q‐ROFIWHM) operators is proposed to support consumers' purchase decisions.
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Investigation of multiple heterogeneous relationships using a q-rung orthopair fuzzy multi-criteria decision algorithm
TL;DR: This work proposes a novel decision algorithm based on q-ROF set to deal with multiple heterogeneous relationships among membership functions and criteria using interactive operators and Maclaurin symmetric mean (MSM) operators.