Accesso libero

Improved Random Forest Fault Diagnosis Model Based on Fault Ratio

INFORMAZIONI SU QUESTO ARTICOLO

Cita

Liu Zhantao Research on integrated method of condition monitoring and fault diagnosis of large equipment system [D] Beijing University of chemical technology, 2009. ZhantaoLiu Research on integrated method of condition monitoring and fault diagnosis of large equipment system [D] Beijing University of chemical technology 2009 Search in Google Scholar

Xiong Fanlun Architecture and implementation of intelligent system technology for agricultural field [J] Pattern recognition and artificial intelligence, 2012, 25 (05): 729–736. FanlunXiong Architecture and implementation of intelligent system technology for agricultural field [J] Pattern recognition and artificial intelligence 2012 25 05 729 736 Search in Google Scholar

Guo Zhi Research on fault diagnosis method of chemical machinery and equipment based on big data [J] Information recording materials, 2021, 22 (09): 233–235. ZhiGuo Research on fault diagnosis method of chemical machinery and equipment based on big data [J] Information recording materials 2021 22 09 233 235 Search in Google Scholar

Zhang Peilin, Cao Jianjun, Ren Guoquan Research on condition monitoring system of large mobile complex equipment [J] Journal of Gun Launch and control, 2006 (03): 15–18. PeilinZhang JianjunCao GuoquanRen Research on condition monitoring system of large mobile complex equipment [J] Journal of Gun Launch and control 2006 03 15 18 Search in Google Scholar

Xu Dongpo, Liu Yunqing, Wang Qian. Random forest-based human pose detection system for through-the-wall radar [J]. Journal of Physics: Conference Series, 2021, 1966(1). DongpoXu YunqingLiu QianWang Random forest-based human pose detection system for through-the-wall radar [J] Journal of Physics: Conference Series 2021 1966 1 Search in Google Scholar

Sherif Ahmed Abu El-Magd, Sk Ajim Ali, Quoc Bao Pham. Spatial modeling and susceptibility zonation of landslides using random forest, naïve bayes and K-nearest neighbor in a complicated terrain [J]. Earth Science Informatics, 2021 (prepublish). Abu El-MagdSherif Ahmed AliSk Ajim PhamQuoc Bao Spatial modeling and susceptibility zonation of landslides using random forest, naïve bayes and K-nearest neighbor in a complicated terrain [J] Earth Science Informatics 2021 (prepublish). Search in Google Scholar

Wu Weijie Research on application and optimization method of random forest algorithm [D] Jiangnan University, 2021. WeijieWu Research on application and optimization method of random forest algorithm [D] Jiangnan University 2021 Search in Google Scholar

Dong Hongyao, Wang Yidan, Li Lihong. Overview of Random Forest Optimization Algorithms [J]. Information and Computer (Theoretical Edition), 2021, 33(17): 34–37. HongyaoDong YidanWang LihongLi Overview of Random Forest Optimization Algorithms [J] Information and Computer (Theoretical Edition) 2021 33 17 34 37 Search in Google Scholar

Sun Mingzhe, Bi Yaojia, Sun Chi. Overview of Improved Random Forest Algorithm [J]. Modern Information Technology, 2019, 3(20): 28–30. MingzheSun YaojiaBi ChiSun Overview of Improved Random Forest Algorithm [J] Modern Information Technology 2019 3 20 28 30 Search in Google Scholar

Wang Yisen, Xia Shutao. Overview of Random Forest Algorithm for Ensemble Learning [J]. Information and Communication Technology, 2018, 12(01): 49–55. YisenWang ShutaoXia Overview of Random Forest Algorithm for Ensemble Learning [J] Information and Communication Technology 2018 12 01 49 55 Search in Google Scholar

eISSN:
2470-8038
Lingua:
Inglese
Frequenza di pubblicazione:
4 volte all'anno
Argomenti della rivista:
Computer Sciences, other