Algorithm Research & Explore
|
App. Res. of Comp. Printed Article
Vol. 40, 2023 No. 4
1012-1018

New ensemble learning method for evidential reasoning based on diversity weighting

Tang Kai1
Li Kangle2
Sun Guowen1
Li Hongyu1
Zhang Yizhe1
He Wei1,3
1. College of Computer Science & Information Engineering, Harbin Normal University, Harbin 150025, China
2. Dept. of Computer Science, Harbin Finance University, Harbin 150030, China
3. Rocket Force University of Engineering, Xi'an 710025, China
DOI: 10.19734/j.issn.1001-3695.2022.08.0429

Abstract

Using the average method and the voting method as a combination strategy can't make full use of the effective information of the base classifiers in ensemble learning, and the weights of base classifiers set with the volatility are imprecise and inappropriate. The above problems will reduce the effect of ensemble learning. In order to further improve the performance of ensemble learning, this paper proposed an ensemble learning method, which used evidence reasoning(ER) rules as a combination strategy and used diversity empowerment method set up the weights of the base classifiers. Firstly, the model used multiple deep learning models as the base classifiers and the ER rules as the combination strategy to construct the basic structure of ensemble learning. Then, it calculated the differences of each base classifier with respect to other base classifiers by the diversity measure method. Finally, it used the results of the differences normalization of the base classifiers as the weights of the base classifiers. Through the classification experiments of multiple image datasets, the experimental results show that the proposed method is more accurate and stable than other methods, which proves that this method can make full use of the effective information of the base classifiers, and the diversity weighting method is more accurate.

Foundation Support

中国博士后科学基金资助项目
黑龙江省自然科学基金资助项目
黑龙江省高等教育教学改革项目

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.08.0429
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 4
Section: Algorithm Research & Explore
Pages: 1012-1018
Serial Number: 1001-3695(2023)04-009-1012-07

Publish History

[2022-11-08] Accepted Paper
[2023-04-05] Printed Article

Cite This Article

汤凯, 李康乐, 孙国文, 等. 一种新的基于多样性赋权证据推理的集成学习方法 [J]. 计算机应用研究, 2023, 40 (4): 1012-1018. (Tang Kai, Li Kangle, Sun Guowen, et al. New ensemble learning method for evidential reasoning based on diversity weighting [J]. Application Research of Computers, 2023, 40 (4): 1012-1018. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

Indexed & Evaluation

  • The Second National Periodical Award 100 Key Journals
  • Double Effect Journal of China Journal Formation
  • the Core Journal of China (Peking University 2023 Edition)
  • the Core Journal for Science
  • Chinese Science Citation Database (CSCD) Source Journals
  • RCCSE Chinese Core Academic Journals
  • Journal of China Computer Federation
  • 2020-2022 The World Journal Clout Index (WJCI) Report of Scientific and Technological Periodicals
  • Full-text Source Journal of China Science and Technology Periodicals Database
  • Source Journal of China Academic Journals Comprehensive Evaluation Database
  • Source Journals of China Academic Journals (CD-ROM Version), China Journal Network
  • 2017-2019 China Outstanding Academic Journals with International Influence (Natural Science and Engineering Technology)
  • Source Journal of Top Academic Papers (F5000) Program of China's Excellent Science and Technology Journals
  • Source Journal of China Engineering Technology Electronic Information Network and Electronic Technology Literature Database
  • Source Journal of British Science Digest (INSPEC)
  • Japan Science and Technology Agency (JST) Source Journal
  • Russian Journal of Abstracts (AJ, VINITI) Source Journals
  • Full-text Journal of EBSCO, USA
  • Cambridge Scientific Abstracts (Natural Sciences) (CSA(NS)) core journals
  • Poland Copernicus Index (IC)
  • Ulrichsweb (USA)