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[HTML][HTML] Representing uncertainty and imprecision in machine learning: A survey on belief functions
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 …
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 …
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 …
resources. However, conventional experimental methods are costly, time-consuming, and …
Estimation of syngas yield in hydrothermal gasification process by application of artificial intelligence models
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 …
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
The recent studies signify the growing concern of researchers towards monitoring and
measuring sustainability performance at various levels and in many fields, including …
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 …
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 …
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 …
information fusion for handing uncertainty problems. However, there may be counter …
Classifying vaguely labeled data based on evidential fusion
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 …
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 …
gig economy (GE) phenomenon, which jointly caused considerable transformations in …