|
Symbols
|
Abbreviations
|
|
K
|
mode number |
ApEn |
approximate entropy |
|
mk
|
set of K mode functions |
ANN |
artificial neural network |
|
ωk
|
set of central frequencies |
ASA |
artificial sheep algorithm |
|
∂t
|
partial derivative of time t
|
BFA |
bacterial foraging algorithm |
|
δt
|
unit pulse function of time t
|
BPNN |
back-propagation neural network |
|
f(t) |
real valued input signal |
CWRU |
Case Western Reserve University |
|
α
|
penalty factor for VMD |
CQSCA |
chaos quantum sine cosine algorithm |
|
β(t) |
Lagrange multiplier for VMD |
DE |
dispersion entropy |
|
w
|
weight vector |
EMD |
empirical mode decomposition |
|
b
|
bias parameter |
EEMD |
ensemble empirical mode decomposition |
|
ξ
|
slack term |
EWT |
empirical wavelet transforms |
|
C
|
penalty factor for SVM |
ELM |
extreme learning machine |
|
g
|
kernel parameter |
FE |
fuzzy entropy |
|
μi
|
Lagrange multiplier for SVM |
FSDE |
fine-sorted dispersion entropy |
|
x
|
time series |
GCMPE |
generalized composite multiscale permutation entropy |
|
n
|
length of time series |
HGSA |
hybrid gravitational search algorithm |
|
σ
|
variance of the normal distribution |
IMPE |
improved multiscale permutation entropy |
|
μ
|
expectation of the normal distribution |
IMDE |
improved multiscale dispersion entropy |
|
|
reconstruction matrix of x
|
IMF |
intrinsic mode function |
|
m
|
embedding dimension |
KNN |
k-nearest neighbour |
|
τ
|
time delay |
LapSVM |
Laplacian support vector machine |
|
c
|
number of class |
LSSVM |
least squares support vector machine |
|
|
class sequence of DE |
MSCAPSO |
mutation sine cosine algorithm and particle swarm optimization |
|
|
dispersion pattern of DE |
MHGWOSCA |
mutation hybrid grey wolf optimizer and sine cosine algorithm |
|
f
|
factor of FSDE |
mRMR |
max-relevance min-redundancy |
|
ρ
|
precision parameter |
MAR |
multivariate autoregressive |
|
|
class sequence of DE |
MAE |
mean absolute error |
|
|
dispersion pattern of FSDE |
MAPE |
root mean square error |
|
Zi
|
position of individual |
PSO |
particle swarm optimization |
|
Pi
|
best position of individual |
PE |
permutation entropy |
|
vi
|
velocity of particle |
QPSO |
quantum behaved particle swarm optimization |
|
si
|
position of particle |
RMSE |
mean absolute percentage error |
|
Pibest
|
individual extreme value |
SCA |
sine cosine algorithm |
|
Pigbest
|
global extreme value |
SVM |
support vector machine |
|
c1, c2
|
learning factor |
SSKMFA |
semi-supervised kernel Marginal Fisher analysis |
|
Zijl
|
position of bottom layer individual |
TSMFE |
time shift multiscale fuzzy entropy |
|
sil
|
position of top layer particle |
VMD |
variational mode decomposition |
|
M
|
number of top layer particle |
|
|
|
N
|
number of bottom layer individual |
|
|
|
G
|
mutation amplitude |
|
|
|
l
|
current number of iterations |
|
|