Research on fault diagnosis of supercharged boiler with limited data based on few-shot learning
G Li, Y Li, C Fang, J Su, H Wang, S Sun, G Zhang, J Shi - Energy, 2023 - Elsevier
The safety of the supercharged boiler affects the normal operation of the steam power
system, while its fault samples are few and contain large noise in reality. Therefore, we …
system, while its fault samples are few and contain large noise in reality. Therefore, we …
Towards sustainable transport: techno-economic analysis of investing in hydrogen buses in public transport in the selected city of Poland
The production, storage, and use of hydrogen for energy purposes will become increasingly
important during the energy transition. One way to use hydrogen is to apply it to power …
important during the energy transition. One way to use hydrogen is to apply it to power …
Enhanced model for predicting student dropouts in developing countries using automated machine learning approach: A case of Tanzanian's Secondary Schools
ABSTRACT The Sub-Saharan countries are leading in dropout rates in secondary schools
by 37.5% followed by South Asia 15.5% and Middle East 11% in 2018. In Tanzania, student …
by 37.5% followed by South Asia 15.5% and Middle East 11% in 2018. In Tanzania, student …
Decision rules derived from optimal decision trees with hypotheses
Conventional decision trees use queries each of which is based on one attribute. In this
study, we also examine decision trees that handle additional queries based on hypotheses …
study, we also examine decision trees that handle additional queries based on hypotheses …
On the depth of decision trees with hypotheses
M Moshkov - Entropy, 2022 - mdpi.com
In this paper, based on the results of rough set theory, test theory, and exact learning, we
investigate decision trees over infinite sets of binary attributes represented as infinite binary …
investigate decision trees over infinite sets of binary attributes represented as infinite binary …
Cost-sensitive classification algorithm combining the Bayesian algorithm and quantum decision tree
N Ji, R Bao, X Mu, Z Chen, X Yang, S Wang - Frontiers in Physics, 2023 - frontiersin.org
This study highlights the drawbacks of current quantum classifiers that limit their efficiency
and data processing capabilities in big data environments. The paper proposes a global …
and data processing capabilities in big data environments. The paper proposes a global …
Random rotboost: An ensemble classification method based on rotation forest and adaboost in random subsets and its application to clinical decision support
In the era of bathing in big data, it is common to see enormous amounts of data generated
daily. As for the medical industry, not only could we collect a large amount of data, but also …
daily. As for the medical industry, not only could we collect a large amount of data, but also …
Applications of Depth Minimization of Decision Trees Containing Hypotheses for Multiple-Value Decision Tables
In this research, we consider decision trees that incorporate standard queries with one
feature per query as well as hypotheses consisting of all features' values. These decision …
feature per query as well as hypotheses consisting of all features' values. These decision …
[图书][B] Decision Trees with Hypotheses
Decision trees are widely used in many areas of computer science and related fields as
classifiers, as a means for knowledge representation, and as algorithms to solve various …
classifiers, as a means for knowledge representation, and as algorithms to solve various …
A Bi-criteria optimization model for adjusting the decision tree parameters
Decision trees play a very important role in knowledge representation because of its
simplicity and self-explanatory nature. We study the optimization of the parameters of the …
simplicity and self-explanatory nature. We study the optimization of the parameters of the …