5,430 research outputs found
A Comparison of GAs Penalizing Infeasible Solutions and Repairing Infeasible Solutions on the 0-1 Knapsack Problem
Constraints exist in almost every optimization problem. Different
constraint handling techniques have been incorporated with genetic
algorithms (GAs), however most of current studies are based on
computer experiments. An example is Michalewicz\u27s comparison among
GAs using different constraint handling techniques on the 0-1
knapsack problem. The following phenomena are observed in
experiments: 1) the penalty method needs more generations to find a
feasible solution to the restrictive capacity knapsack than the
repair method; 2) the penalty method can find
better solutions to the average capacity knapsack. Such observations
need a theoretical explanation. This paper aims at providing a
theoretical analysis of Michalewicz\u27s experiments. The main result
of the paper is that GAs using the repair method are more efficient
than GAs using the penalty method on both restrictive capacity and
average capacity knapsack problems. This result of the average
capacity is a little different from Michalewicz\u27s experimental
results. So a supplemental experiment is implemented to support the
theoretical claim. The results confirm the general principle pointed
out by Coello: a better constraint-handling approach should tend to
exploit specific domain knowledge
Filament L1482 in the California molecular cloud
Aims. The process of gravitational fragmentation in the L1482 molecular
filament of the California molecular cloud is studied by combining several
complementary observations and physical estimates. We investigate the kinematic
and dynamical states of this molecular filament and physical properties of
several dozens of dense molecular clumps embedded therein.
Methods. We present and compare molecular line emission observations of the
J=2--1 and J=3--2 transitions of 12CO in this molecular complex, using the
KOSMA 3-meter telescope. These observations are complemented with archival data
observations and analyses of the 13CO J=1--0 emission obtained at the Purple
Mountain Observatory 13.7-meter radio telescope at Delingha Station in QingHai
Province of west China, as well as infrared emission maps from the Herschel
Space Telescope online archive, obtained with the SPIRE and PACS cameras.
Comparison of these complementary datasets allow for a comprehensive
multi-wavelength analysis of the L1482 molecular filament.
Results. We have identified 23 clumps along the molecular filament L1482 in
the California molecular cloud. All these molecular clumps show supersonic
non-thermal gas motions. While surprisingly similar in mass and size to the
much better known Orion molecular cloud, the formation rate of high-mass stars
appears to be suppressed in the California molecular cloud relative to that in
the Orion molecular cloud based on the mass-radius threshold derived from the
static Bonnor Ebert sphere. Our analysis suggests that these molecular
filaments are thermally supercritical and molecular clumps may form by
gravitational fragmentation along the filament. Instead of being static, these
molecular clumps are most likely in processes of dynamic evolution.Comment: 10 pages, 9 figures, 2 tables, accepted to Astronomy and Astrophysic
A Study of Fermi-LAT GeV gamma-ray Emission towards the Magnetar-harboring Supernova Remnant Kesteven 73 and Its Molecular Environment
We report our independent GeV gamma-ray study of the young shell-type
supernova remnant (SNR) Kes 73 which harbors a central magnetar, and CO-line
millimeter observations toward the SNR. Using 7.6 years of Fermi-LAT
observation data, we detected an extended gamma-ray source ("source A") with
the centroid on the west of the SNR, with a significance of 21.6 sigma in
0.1-300 GeV and an error circle of 5.4 arcminute in angular radius. The
gamma-ray spectrum cannot be reproduced by a pure leptonic emission or a pure
emission from the magnetar, and thus a hadronic emission component is needed.
The CO-line observations reveal a molecular cloud (MC) at V_LSR~90 km/s, which
demonstrates morphological correspondence with the western boundary of the SNR
brightened in multiwavelength. The 12CO (J=2-1)/12CO (J=1-0) ratio in the left
(blue) wing 85-88 km/s is prominently elevated to ~1.1 along the northwestern
boundary, providing kinematic evidence of the SNR-MC interaction. This SNR-MC
association yields a kinematic distance 9 kpc to Kes 73. The MC is shown to be
capable of accounting for the hadronic gamma-ray emission component. The
gamma-ray spectrum can be interpreted with a pure hadronic emission or a
magnetar+hadronic hybrid emission. In the case of pure hadronic emission, the
spectral index of the protons is 2.4, very similar to that of the
radio-emitting electrons, essentially consistent with the diffusive shock
acceleration theory. In the case of magnetar+hadronic hybrid emission, a
magnetic field decay rate >= 10^36 erg/s is needed to power the magnetar's
curvature radiation.Comment: 7 figures, published in Ap
Robust Estimation and Inference for Expected Shortfall Regression with Many Regressors
Expected Shortfall (ES), also known as superquantile or Conditional
Value-at-Risk, has been recognized as an important measure in risk analysis and
stochastic optimization, and is also finding applications beyond these areas.
In finance, it refers to the conditional expected return of an asset given that
the return is below some quantile of its distribution. In this paper, we
consider a recently proposed joint regression framework that simultaneously
models the quantile and the ES of a response variable given a set of
covariates, for which the state-of-the-art approach is based on minimizing a
joint loss function that is non-differentiable and non-convex. This inevitably
raises numerical challenges and limits its applicability for analyzing
large-scale data. Motivated by the idea of using Neyman-orthogonal scores to
reduce sensitivity with respect to nuisance parameters, we propose a
statistically robust (to highly skewed and heavy-tailed data) and
computationally efficient two-step procedure for fitting joint quantile and ES
regression models. With increasing covariate dimensions, we establish explicit
non-asymptotic bounds on estimation and Gaussian approximation errors, which
lay the foundation for statistical inference. Finally, we demonstrate through
numerical experiments and two data applications that our approach well balances
robustness, statistical, and numerical efficiencies for expected shortfall
regression
Application of EMD-WVD and particle filter for gearbox fault feature extraction and remaining useful life prediction
Fault feature extraction and remaining useful life (RUL) prediction are important to condition based maintenance (CBM). In order to realize the fault feature extraction of gearbox vibration signal presenting nonlinear and non-Gaussian, the integration of empirical mode decomposition (EMD) and Wigner-Ville distribution (WVD) are proposed in this paper. Taking the kurtosis as standard, the WVD is applied to some IMFs with larger kurtosis to calculate the time-frequency distribution, with an effective suppress on mode mixing and the cross-term interference. Afterwards, particle filter (PF) with the state space model based on Wiener process is proposed to predict the RUL of gearbox considering degradation feature, gearbox teeth wear and nonlinear and non-Gaussian system. The gearbox life cycle test shows that the EMD-WVD method can extract the valued characteristics of vibration signal accurately, and the particle filter can provide an effective way to predict the RUL of gearbox
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