[HTML][HTML] Representing uncertainty and imprecision in machine learning: A survey on belief functions

Z Liu, S Letchmunan - Journal of King Saud University-Computer and …, 2024 - Elsevier
Uncertainty and imprecision accompany the world we live in and occur in almost every
event. How to better interpret and manage uncertainty and imprecision play a vital role in …

Combining time-series evidence: A complex network model based on a visibility graph and belief entropy

X Song, F **ao - Applied Intelligence, 2022 - Springer
Combining basic probability assignments (BPAs) with time series is common in real-life
cases. Therefore, a new evidence fusion approach based on belief entropy and a visibility …

A hybrid data-driven machine learning framework for predicting the performance of coal and biomass gasification processes

Q Yang, J Zhang, J Zhou, L Zhao, D Zhang - Fuel, 2023 - Elsevier
Gasification technology can effectively improve the utilization efficiency of coal and biomass
resources. However, conventional experimental methods are costly, time-consuming, and …

Estimation of syngas yield in hydrothermal gasification process by application of artificial intelligence models

Y Ayub, Y Hu, J Ren - Renewable Energy, 2023 - Elsevier
Quality syngas production with higher moles of hydrogen and methane are the primary
objective of gasification process which is dependent upon the process parameters and …

[HTML][HTML] A Strong Sustainability Paradigm based Analytical Hierarchy Process (SSP-AHP) method to evaluate sustainable healthcare systems

J Wątróbski, A Bączkiewicz, I Rudawska - Ecological Indicators, 2023 - Elsevier
The recent studies signify the growing concern of researchers towards monitoring and
measuring sustainability performance at various levels and in many fields, including …

RBMDO Using Gaussian Mixture Model-Based Second-Order Mean-Value Saddlepoint Approximation.

D Meng, S Yang, T Lin, J Wang… - … -Computer Modeling in …, 2022 - search.ebscohost.com
Actual engineering systems will be inevitably affected by uncertain factors. Thus, the
Reliability-Based Multidisciplinary Design Optimization (RBMDO) has become a hotspot for …

A novel combination rule for conflict management in data fusion

X Chen, Y Deng - Soft Computing, 2023 - Springer
How to handle conflict in Dempster-Shafer evidence theory is an open issue. Many
approaches have been proposed to solve this problem. The existing approaches can be …

A novel belief χ 2 χ^2 divergence for multisource information fusion and its application in pattern classification

L Zhang, F **ao - International Journal of Intelligent Systems, 2022 - Wiley Online Library
Abstract Dempster–Shafer (D‐S) evidence theory is invaluable in the domain of multisource
information fusion for handing uncertainty problems. However, there may be counter …

Classifying vaguely labeled data based on evidential fusion

M Song, C Sun, D Cai, S Hong, H Li - Information Sciences, 2022 - Elsevier
Classification is one of the fundamental supervised learning tasks which learns classifiers
from the given training data and related labels. The quality of labels is important in …

What matters in hiring professionals for global software development? A SLR and NLP criteria clustering

EA dos Santos, DGB de Souza… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Globalization stimulated a new era of Global Software Development (GSD), followed by the
gig economy (GE) phenomenon, which jointly caused considerable transformations in …