화학공학소재연구정보센터
검색결과 : 91건
No. Article
1 Incipient fault diagnosis for centrifugal chillers using kernel entropycomponent analysis and voting based extreme learning machine
Xia Y, Ding Q, Jiang A, Jing N, Zhoug W, Wang J
Korean Journal of Chemical Engineering, 39(3), 504, 2022
2 Color difference classification of dyed fabrics via a kernel extreme learning machine based on an improved grasshopper optimization algorithm
Li JQ, Shi WM, Yang DH
Color Research and Application, 46(2), 388, 2021
3 A Note on the Numerical Solutions of Kernel-Based Learning Problems
Scandella M, Mazzoleni M, Formentin S, Previdi F
IEEE Transactions on Automatic Control, 66(2), 940, 2021
4 State of health prediction for lithium-ion batteries with a novel online sequential extreme learning machine method
Tian HX, Qin PL
International Journal of Energy Research, 45(2), 2383, 2021
5 Multi-step wind speed forecast based on sample clustering and an optimized hybrid system
Chen XJ, Zhao J, Jia XZ, Li ZL
Renewable Energy, 165, 595, 2021
6 A hybrid approach for multi-step wind speed forecasting based on two-layer decomposition, improved hybrid DE-HHO optimization and KELM
Fu WL, Zhang K, Wang K, Wen B, Fang P, Zou F
Renewable Energy, 164, 211, 2021
7 Numerical modeling of SiC by low-pressure chemical vapor deposition from methyltrichlorosilane
Guan K, Gao Y, Zeng QF, Luan XG, Zhang Y, Cheng LF, Wu JQ, Lu ZY
Chinese Journal of Chemical Engineering, 28(6), 1733, 2020
8 Prediction of effluent quality in papermaking wastewater treatment processes using dynamic kernel-based extreme learning machine
Liu HB, Zhang YC, Zhang H
Process Biochemistry, 97, 72, 2020
9 Ultrasound-assisted process optimization and tribological characteristics of biodiesel from palm-sesame oil via response surface methodology and extreme learning machine - Cuckoo search
Mujtaba MA, Masjuki HH, Kalam MA, Ong HC, Gul M, Farooq M, Soudagar MEM, Ahmed W, Harith MH, Yusoff MNAM
Renewable Energy, 158, 202, 2020
10 Negative correlation learning-based RELM ensemble model integrated with OVMD for multi-step ahead wind speed forecasting
Peng T, Zhang C, Zhou JZ, Nazir MS
Renewable Energy, 156, 804, 2020