Suchergebnisse - "stacking integration algorithm"

Rockburst Intensity Classification Prediction Based on Multi-Model Ensemble Learning Algorithms

Autoren: Jiachuang Wang Haoji Ma Xianhang Yan

Quelle: Mathematics, Vol 11, Iss 4, p 838 (2023)

Schlagwörter: rockburst prediction, stacking integration algorithm, voting integration algorithm, SMOTE data oversampling, fusion strategy, Mathematics, QA1-939

Relation: https://www.mdpi.com/2227-7390/11/4/838; https://doaj.org/toc/2227-7390; https://doaj.org/article/b9c4950719cd4f45823a195aa3227d9a

Verfügbarkeit: https://doi.org/10.3390/math11040838
https://doaj.org/article/b9c4950719cd4f45823a195aa3227d9a

Research on Sinter Quality Prediction System Based on Granger Causality Analysis and Stacking Integration Algorithm

Autoren: Xin Li Xiaojie Liu Hongyang Li et al.

Quelle: Metals, Vol 13, Iss 2, p 419 (2023)

Schlagwörter: sintering quality, Granger causality analysis, stacking integration algorithm, Mining engineering. Metallurgy, TN1-997

Relation: https://www.mdpi.com/2075-4701/13/2/419; https://doaj.org/toc/2075-4701; https://doaj.org/article/eaf646d2c34846b5930665378e7073f1

Verfügbarkeit: https://doi.org/10.3390/met13020419
https://doaj.org/article/eaf646d2c34846b5930665378e7073f1

Fault Diagnosis of Wind Turbine Generators Based on Stacking Integration Algorithm and Adaptive Threshold

Autoren: Zhanjun Tang Xiaobing Shi Huayu Zou et al.

Quelle: Sensors, Vol 23, Iss 13, p 6198 (2023)

Schlagwörter: fault diagnosis, WTG, stacking integration algorithm, machine learning, EDP, adaptive threshold, Chemical technology, TP1-1185

Relation: https://www.mdpi.com/1424-8220/23/13/6198; https://doaj.org/toc/1424-8220; https://doaj.org/article/940c68cc10af4cacb745c17ae9238642

Verfügbarkeit: https://doi.org/10.3390/s23136198
https://doaj.org/article/940c68cc10af4cacb745c17ae9238642

Vibration Test of Single Coal Gangue Particle Directly Impacting the Metal Plate and the Study of Coal Gangue Recognition Based on Vibration Signal and Stacking Integration

Autoren: Yang Yang Qingliang Zeng Guangjun Yin et al.

Quelle: IEEE Access, Vol 7, Pp 106784-106805 (2019)

Schlagwörter: Coal gangue recognition, intercepted signal, stacking integration algorithm, vibration signal, EMD, impact, 0202 electrical engineering, electronic engineering, information engineering, Electrical engineering. Electronics. Nuclear engineering, 02 engineering and technology, 01 natural sciences, TK1-9971, 0105 earth and related environmental sciences

Zugangs-URL: https://ieeexplore.ieee.org/ielx7/6287639/8600701/08782521.pdf
https://doaj.org/article/ae04beb04c7f419c9f3d88433e685127