|
[1] SUN K,
ZHANG J S, ZHANG C X, et al. Generalized extreme
learning
machine autoencoder and a new deep neural network.
Neurocomputing,
2017, 230: 374 -381.
[2] LI J J, XI
B B, DU Q, et al. Deep kernel extreme-learning
machine for
the spectral-spatial classification of hyperspectral
imagery.
Remote Sensing, 2018, 10(12): Article 2036.
[3] DU G Y, XU
Q, YANG X Y. Fault diagnosis of rotating
machinery
components using a deep kernel extreme learning
machine under
different working conditions. Measurement Science
and
Technology, 2020, 31(11): Article 115901.
[4] KHAN M A,
KADRY S, PARWEKAR P, et al. Human gait
analysis for
osteoarthritis prediction: A framework of deep learning
and kernel
extreme learning machine. Complex & Intelligent
Systems, 2021,
9: 2665 -2683.
[5] LI D P.
Automatic detection of cardiovascular disease using deep
kernel extreme
learning machine. Biomedical Engineering:
Applications,
Basis and Communications, 2018, 30(6): Article
1850038.
[6] HUANG G B,
ZHU Q Y, SIEW C K. Extreme learning machine:
Theory and
applications. Neurocomputing, 2006, 70 (1/2/3):
489 -501.
[7] WANG J, LU
S Y, WANG S H, et al. A review on extreme
learning
machine. Multimedia Tools and Applications, 2022, 81:
41611 -41660.
[8] MURUGAN R,
GOEL T. E-DiCoNet: Extreme learning machine
based
classifier for diagnosis of COVID-19 using deep
convolutional
network. Journal of Ambient Intelligence and
Humanized
Computing, 2021, 12(9): 8887 -8898.
[9] IOSIFIDIS
A, TEFAS A, PITAS I. On the kernel extreme learning
machine
classifier. Pattern Recognition Letters, 2015, 54: 11 -17.
[10] HUANG G,
HUANG G B, SONG S J, et al. Trends in extreme
learning
machines: A review. Neural Networks, 2015, 61: 32 -48.
[11] TANG J X,
DENG C W, HUANG G B. Extreme learning machine
for multilayer
perceptron. IEEE Transactions on Neural Networks
and Learning
Systems, 2016, 27(4): 809 -821.
[12] AFZAL A
L, NAIR N K, ASHARAF S. Deep kernel learning in
extreme
learning machines. Pattern Analysis and Applications,
2021, 24(1):
11 -19.
[13] DING S F,
ZHANG N, XU X Z, et al. Deep extreme learning
machine and
its application in EEG classification. Mathematical
Problems in
Engineering, 2015: Article 129021.
[14] XIA J F,
YANG D Q, ZHOU H, et al. Evolving kernel extreme
learning
machine for medical diagnosis via a disperse foraging sine
cosine
algorithm. Computers in Biology and Medicine, 2022,
141(C):
Article 105137.
[15] NIU W J,
FENG Z K, JIANG Z Q, et al. Enhanced harmony
search
algorithm for sustainable ecological operation of cascade
hydropower
reservoirs in river ecosystem. Environmental Research
Letters, 2021,
16(5): Article 055013.
[16] DALAL S,
VISHWAKARMA V P. GA based KELM optimization
for ECG
classification. Procedia Computer Science, 2020, 167:
580 -588.
[17] ZHAO Z N,
DUAN W, CAI G J. A novel PSO-KELM based soil
liquefaction
potential evaluation system using CPT and Vs
measurements.
Soil Dynamics and Earthquake Engineering, 2021,
150: Article
106930.
[18] FAN Y Y,
WANG H C, ZHAO X Y, et al. Short-term load
forecasting of
distributed energy system based on kernel principal
component
analysis and KELM optimized by fireworks algorithm.
Applied Sciences,
2021, 11(24): Article 12014.
[19] YANG Z,
SUN Z W. Research on geographic location prediction
algorithm
based on improved teaching and learning optimization
ELM. Frontiers
in Physics, 2020, 259: 1 -8.
[20] WUMAIER
T, XU C, GUO H Y, et al. Fault diagnosis of wind
turbines based
on a support vector machine optimized by the sparrow
search
algorithm. IEEE Access, 2021, 9: 69307 -69315.
[21] XUE J K,
SHEN B. A novel swarm intelligence optimization
approach:
Sparrow search algorithm. Systems Science & Control
Engineering,
2020, 8(1): 22 -34.
[22] YANG L,
LI Z, WANG D S, et al. Software defects prediction
based on
hybrid particle swarm optimization and sparrow search
algorithm.
IEEE Access, 2021, 9: 60865 -60879.
[23] YUAN J H,
ZHAO Z W, LIU Y P, et al. DMPPT control of
photovoltaic
microgrid based on improved sparrow search
algorithm.
IEEE Access, 2021, 9: 16623 -16629.
[24] WANG H Z,
WU X R, GHOLINIA F. Forecasting hydropower
generation by
GFDL-CM3 climate model and hybrid hydrological-
Elman neural
network model based on improved sparrow search
algorithm
(ISSA). Concurrency and Computation: Practice and
Experience,
2021, 33(24): Article e6476.
[25] ZHANG C
L, DING S F. A stochastic configuration network based
on chaotic
sparrow search algorithm. Knowledge-Based Systems,
2021, 220:
Article 106924.
[26] FENG B F,
XU Y S, ZHANG T, et al. Hydrological time series
prediction by
extreme learning machine and sparrow search
algorithm.
Water Supply, 2022, 22(3): 3143 -3157.
[27] ZOU W D,
LI Y X, XIA Y Q. Extreme learning machine based on
state
transition algorithm. Journal of Beijing Institute of
Technology,
2022, 42(10): 1042 -1050 (in Chinese).
[28] YANG J C,
SHI R, NI B B. MedMNIST classification decathlon:
A lightweight
automl benchmark for medical image analysis.
Proceedings of
the IEEE 18th International Symposium on
Biomedical
Imaging ( ISBI'21 ), 2021, Apr 13 - 16, Nice,
France.
Piscataway, NJ, USA: IEEE, 2021: 191 -195.
[29] LAI J,
WANG X D, LI R, et al. BD-ELM: A regularized extreme
learning
machine using biased dropConnect and biased dropout.
Mathematical
Problems in Engineering, 2020: Article 3604579.
[30] ZHANG W
Y, ZHANG Z J, WANG L F, et al. Extreme learning
machines with
expectation kernels. Pattern Recognition, 2019,
96: Article 106960.
|
