scholarly journals An Ensemble Learning Approach for Fault Diagnosis in Self-Organizing Heterogeneous Networks

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 125662-125675 ◽  
Author(s):  
Yueping Wang ◽  
Kun Zhu ◽  
Mengyun Sun ◽  
Yueyu Deng
Keyword(s):  
Fault Diagnosis ◽  
Ensemble Learning ◽  
Heterogeneous Networks ◽  
Learning Approach ◽  
Self Organizing

Ensemble Learning Approach with LASSO for Predicting Catalytic Reaction Rates

Synlett ◽  
2020 ◽  
Author(s):  
Akira Yada ◽  
Kazuhiko Sato ◽  
Tarojiro Matsumura ◽  
Yasunobu Ando ◽  
Kenji Nagata ◽  
...  
Keyword(s):  
Ensemble Learning ◽  
Reaction Rates ◽  
Initial Reaction Rate ◽  
Training Dataset ◽  
Initial Reaction ◽  
Learning Approach ◽  
Learning Framework ◽  
Machine Learning Approach ◽  
Reasonable Prediction ◽  
Epoxidation Of Alkenes

AbstractThe prediction of the initial reaction rate in the tungsten-catalyzed epoxidation of alkenes by using a machine learning approach is demonstrated. The ensemble learning framework used in this study consists of random sampling with replacement from the training dataset, the construction of several predictive models (weak learners), and the combination of their outputs. This approach enables us to obtain a reasonable prediction model that avoids the problem of overfitting, even when analyzing a small dataset.

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