Mode angular degree identification in subgiant stars with convolutional neural networks based on power spectrum

Du, Minghao; Bi, Shaolan; Zhang, Xianfei; Li, Yaguang; Li, Tanda; Shi, Ruihan

doi:10.1093/mnras/staa3642

Cited by 3 publications

(2 citation statements)

References 44 publications

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“…e larger and deeper the foundation pit project, the more difficult it will be for the support structure of the foundation pit project [25].…”

Section: Construction Of the Spatial Topological Relationship Ofmentioning

confidence: 99%

Deformation Detection Model of High-Rise Building Foundation Pit Support Structure Based on Neural Network and Wireless Communication

Ding

2021

Security and Communication Networks

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The reasonable selection and optimized design of the deep foundation pit support scheme is directly related to the safety, construction period, and cost of the entire project. Here, based on a large number of theoretical results in many related fields, relevant influencing factors are systematically analyzed, and advanced mathematical algorithms such as neural networks are introduced according to the relevant characteristics of building deep foundation pit support construction. First of all, this paper designs and implements deep foundation pit construction safety risk technology based on wireless communication and BIM technology and analyzes and describes the framework and function of the foundation pit construction safety risk identification system. Secondly, we use neural network algorithms to study the deformation prediction of the foundation pit supporting structure, which can describe the expression method of the above safety knowledge. Finally, the differences and benefits of this method and traditional methods are compared through experiments, which show that this technology can pave the way for the construction of deep foundation pit construction safety risk knowledge.

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“…e larger and deeper the foundation pit project, the more difficult it will be for the support structure of the foundation pit project [25].…”

Section: Construction Of the Spatial Topological Relationship Ofmentioning

confidence: 99%

Deformation Detection Model of High-Rise Building Foundation Pit Support Structure Based on Neural Network and Wireless Communication

Ding

2021

Security and Communication Networks

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“…The ReLU function can alleviate the problem of vanishing gradients in the neural network. The dropout technique was introduced to prevent overfitting [73,74]. By relying on the powerful prediction performance of onedimensional convolution [75] and using the data set obtained by finite element analysis to train 1D-CNN, a model equivalent to the overdetermined equation can be obtained.…”

Section: The Potential For Ann Use In Ioamentioning

confidence: 99%

A Review on Zernike Coefficient-Solving Algorithms (CSAs) Used for Integrated Optomechanical Analysis (IOA)

Pan

Zhang

et al. 2023

Photonics

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An integrated optomechanical analysis (IOA) can predict the response of an optomechanical system to temperature, gravity, vibrations, and other local loadings; thus, the normal operation of instruments under special conditions is guaranteed. Zernike polynomials are the most popular for fitting the IOA-derived mechanical deformation data. By solving the Zernike coefficients of all deformed optical surfaces, the relationship between aberrations and deformations can be further revealed. The process of IOA is summarized in this article. The principles of four primary Zernike coefficient-solving algorithms (CSAs) were expounded, and the corresponding applications are reviewed in detail, including the least squares method, the Gram–Schmidt orthogonalized method, the Householder transformation, and singular value decomposition (SVD). Artificial neural networks (ANNs) trained for solving a similar overdetermined set of equations are also discussed; an innovative Zernike CSA based on a one-dimensional convolutional neural network (1D-CNN) was proposed, emphasizing its potential for Zernike CSA. The feasibility of the neural network method was verified by conducting experiments on the primary mirror of the front reflection system of a space camera. This review can provide references for the precise optimization of IOA.

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Relations between the asteroseismic indices and stellar parameters of δ Scuti stars for two years of TESS mission

Hasanzadeh

Safari

Ghasemi

2021

Monthly Notices of the Royal Astronomical Society

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We investigate the relationship between the asteroseismic indices and the physical quantities of 438 δ Scuti (DSCT) stars observed by the Transiting Exoplanet Survey Satellite (TESS) mission at 26 sectors. We study the scaling relations of stellar parameters (effective temperature, surface gravity, density, etc.) and asteroseismic indices such as fundamental frequency, large frequency separation (Δν), frequency of the highest peak in the spectrum, and the peak of the envelope of oscillation mode (νmax) for DSCT targets. Using an empirical relation and a two-dimensional autocorrelation method, we determine the large frequency separation for targets. We obtain a highly positive correlation between the fundamental radial pressure mode and the large separation for one-third of targets. We find a scaling relation between the large separation and νmax as $\Delta \nu =0.49\nu _{\rm max}^{0.68}$, which is similar to that of the solar-like and red giant stars. We show a strong positive correlation between the effective temperature and νmax (Pearson correlation R=0.65). We also obtain a very strong positive correlation (R=0.86) between the effective temperature multiplying by the surface gravity and νmax.

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Mode angular degree identification in subgiant stars with convolutional neural networks based on power spectrum

Cited by 3 publications

References 44 publications

Deformation Detection Model of High-Rise Building Foundation Pit Support Structure Based on Neural Network and Wireless Communication

Deformation Detection Model of High-Rise Building Foundation Pit Support Structure Based on Neural Network and Wireless Communication

A Review on Zernike Coefficient-Solving Algorithms (CSAs) Used for Integrated Optomechanical Analysis (IOA)

Relations between the asteroseismic indices and stellar parameters of δ Scuti stars for two years of TESS mission

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