188 related articles for article (PubMed ID: 35115585)
1. Novel ensemble intelligence methodologies for rockburst assessment in complex and variable environments.
Li D; Liu Z; Armaghani DJ; Xiao P; Zhou J
Sci Rep; 2022 Feb; 12(1):1844. PubMed ID: 35115585
[TBL] [Abstract][Full Text] [Related]
2. Ensemble stacking rockburst prediction model based on Yeo-Johnson, K-means SMOTE, and optimal rockburst feature dimension determination.
Sun L; Hu N; Ye Y; Tan W; Wu M; Wang X; Huang Z
Sci Rep; 2022 Sep; 12(1):15352. PubMed ID: 36097043
[TBL] [Abstract][Full Text] [Related]
3. Optimizing Skin Cancer Survival Prediction with Ensemble Techniques.
Abbasi EY; Deng Z; Magsi AH; Ali Q; Kumar K; Zubedi A
Bioengineering (Basel); 2023 Dec; 11(1):. PubMed ID: 38247920
[TBL] [Abstract][Full Text] [Related]
4. Intelligent prediction of rockburst in tunnels based on back propagation neural network integrated beetle antennae search algorithm.
Li G; Xue Y; Qu C; Qiu D; Wang P; Liu Q
Environ Sci Pollut Res Int; 2023 Mar; 30(12):33960-33973. PubMed ID: 36502473
[TBL] [Abstract][Full Text] [Related]
5. LIME-based ensemble machine for predicting performance status of patients with liver cancer.
Nguyen HV; Byeon H
Digit Health; 2023; 9():20552076231211636. PubMed ID: 38025102
[TBL] [Abstract][Full Text] [Related]
6. A prediction model on rockburst intensity grade based on variable weight and matter-element extension.
Chen J; Chen Y; Yang S; Zhong X; Han X
PLoS One; 2019; 14(6):e0218525. PubMed ID: 31242202
[TBL] [Abstract][Full Text] [Related]
7. Application of KNN-based isometric mapping and fuzzy c-means algorithm to predict short-term rockburst risk in deep underground projects.
Kamran M; Ullah B; Ahmad M; Sabri MMS
Front Public Health; 2022; 10():1023890. PubMed ID: 36339170
[TBL] [Abstract][Full Text] [Related]
8. A GA-stacking ensemble approach for forecasting energy consumption in a smart household: A comparative study of ensemble methods.
Dostmohammadi M; Pedram MZ; Hoseinzadeh S; Garcia DA
J Environ Manage; 2024 Jul; 364():121264. PubMed ID: 38870783
[TBL] [Abstract][Full Text] [Related]
9. Ensemble Learning for Disease Prediction: A Review.
Mahajan P; Uddin S; Hajati F; Moni MA
Healthcare (Basel); 2023 Jun; 11(12):. PubMed ID: 37372925
[TBL] [Abstract][Full Text] [Related]
10. A data-driven interpretable ensemble framework based on tree models for forecasting the occurrence of COVID-19 in the USA.
Zheng HL; An SY; Qiao BJ; Guan P; Huang DS; Wu W
Environ Sci Pollut Res Int; 2023 Jan; 30(5):13648-13659. PubMed ID: 36131178
[TBL] [Abstract][Full Text] [Related]
11. Using a stacked ensemble learning framework to predict modulators of protein-protein interactions.
Gao M; Zhao L; Zhang Z; Wang J; Wang C
Comput Biol Med; 2023 Jul; 161():107032. PubMed ID: 37230018
[TBL] [Abstract][Full Text] [Related]
12. Bus Single-Trip Time Prediction Based on Ensemble Learning.
Huang H; Huang L; Song R; Jiao F; Ai T
Comput Intell Neurosci; 2022; 2022():6831167. PubMed ID: 35990123
[TBL] [Abstract][Full Text] [Related]
13. Do we need different machine learning algorithms for QSAR modeling? A comprehensive assessment of 16 machine learning algorithms on 14 QSAR data sets.
Wu Z; Zhu M; Kang Y; Leung EL; Lei T; Shen C; Jiang D; Wang Z; Cao D; Hou T
Brief Bioinform; 2021 Jul; 22(4):. PubMed ID: 33313673
[TBL] [Abstract][Full Text] [Related]
14. Predictive modeling of blood pressure during hemodialysis: a comparison of linear model, random forest, support vector regression, XGBoost, LASSO regression and ensemble method.
Huang JC; Tsai YC; Wu PY; Lien YH; Chien CY; Kuo CF; Hung JF; Chen SC; Kuo CH
Comput Methods Programs Biomed; 2020 Oct; 195():105536. PubMed ID: 32485511
[TBL] [Abstract][Full Text] [Related]
15. Prediction of gross calorific value from coal analysis using decision tree-based bagging and boosting techniques.
Munshi TA; Jahan LN; Howladar MF; Hashan M
Heliyon; 2024 Jan; 10(1):e23395. PubMed ID: 38169874
[TBL] [Abstract][Full Text] [Related]
16. Performance of Machine Learning-Based Multi-Model Voting Ensemble Methods for Network Threat Detection in Agriculture 4.0.
Peppes N; Daskalakis E; Alexakis T; Adamopoulou E; Demestichas K
Sensors (Basel); 2021 Nov; 21(22):. PubMed ID: 34833551
[TBL] [Abstract][Full Text] [Related]
17. Identification of Orphan Genes in Unbalanced Datasets Based on Ensemble Learning.
Gao Q; Jin X; Xia E; Wu X; Gu L; Yan H; Xia Y; Li S
Front Genet; 2020; 11():820. PubMed ID: 33133122
[TBL] [Abstract][Full Text] [Related]
18. BBB-PEP-prediction: improved computational model for identification of blood-brain barrier peptides using blending position relative composition specific features and ensemble modeling.
Naseem A; Alturise F; Alkhalifah T; Khan YD
J Cheminform; 2023 Nov; 15(1):110. PubMed ID: 37980534
[TBL] [Abstract][Full Text] [Related]
19. Virtual metrology of semiconductor PVD process based on combination of tree-based ensemble model.
Chen CH; Zhao WD; Pang T; Lin YZ
ISA Trans; 2020 Aug; 103():192-202. PubMed ID: 32276727
[TBL] [Abstract][Full Text] [Related]
20. Ensemble Machine Learning of Gradient Boosting (XGBoost, LightGBM, CatBoost) and Attention-Based CNN-LSTM for Harmful Algal Blooms Forecasting.
Ahn JM; Kim J; Kim K
Toxins (Basel); 2023 Oct; 15(10):. PubMed ID: 37888638
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]