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Author:

Wang, R. (Wang, R..) | Hu, H. (Hu, H..) | Qi, X. (Qi, X..)

Indexed by:

EI Scopus

Abstract:

In order to propose an effective machine learning prediction model. This paper constructs an ensemble learning prediction model based on a support vector machine (SVM), classification regression tree (CART), and multi-layer perceptual base (MLP), applying R^2 and RMSE to measure the accuracy of the prediction model and compares three The performance of the base learner. The results show that: (1) the RMSE and other parameters of the ensemble learning are small, the R2 is larger, and the prediction effect is significantly higher than that of the basic learner (2) the ensemble learning model based on SVM-CART-MLP has three-time intervals R2 and RMSE. Performance 0.98 vs 0.135.These models have strong general and scalable conditions.  © 2023 IEEE.

Keyword:

MPL CART coal consumption forecast SVM EL

Author Community:

  • [ 1 ] [Wang R.]Chongqing University of Posts and Telecommunications, Chongqing, 400000, China
  • [ 2 ] [Hu H.]Beijing University of Technology, Beijing, 100124, China
  • [ 3 ] [Qi X.]Beijing University of Technology, Beijing, 100124, China

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Year: 2023

Page: 800-804

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 4

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