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1.
科学评价大学生科研创新能力对我国科研水平的提高具有重要意义.采用机器学习模型来预测大学生科研能力可以起到良好的效果,提出一种GAXGBoost模型来实现对大学生的科研能力预测.此模型是以Xgboost算法为基础,然后充分利用遗传算法的全局搜索能力自动搜索Xgboost最优超参数,避免了人为经验调参不准确的缺陷,最后采用精英选择策略以此确保每一轮都是最佳的进化结果.通过分析表明,所采用的GAXGBoost模型在大学生科研能力预测的结果中具有很高的精度,将此模型与Logistic Regression、Random Forest、SVM等模型进行对比,GAXGBoost模型的预测精度最高. 相似文献
2.
In this article, we construct and analyze a residual-based a posteriori error estimator for a quadratic finite volume method (FVM) for solving nonlinear elliptic partial differential equations with homogeneous Dirichlet boundary conditions. We shall prove that the a posteriori error estimator yields the global upper and local lower bounds for the norm error of the FVM. So that the a posteriori error estimator is equivalent to the true error in a certain sense. Numerical experiments are performed to illustrate the theoretical results. 相似文献
3.
Despite significant advances in first-principles calculation methods, there is no single exchange-correlation functional which predicts the ground state of materials without an error yet. We investigated how accurately ground states of binary semiconductors are described using 16 exchange-correlation functionals (with or without van der Waals corrections). LDA, PBEsol, SCAN (with or without rVV10 correction), and PBE with D3 van der Waals correction (zero or Becke-Johnson damping) show good predicting power. The lattice constants of stable phases were slightly better described by SCAN, PBEsol, PBE+D3 (Becke-Johnson damping), and MS2. We also propose a set of functionals to double-check the stability of new materials based on the majority vote. 相似文献
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We study the mean square of the error term of the mean value for binary Egyptian fractions.We get an asymptotic formula under the Riemann Hypothesis. 相似文献
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Time integration of Fourier pseudospectral DNS is usually performed using the classical fourth-order accurate Runge-Kutta method or other second- or third-order methods, with a fixed step size. We investigate the use of higher-order Runge-Kutta pairs and automatic step size control based on local error estimation. We find that the fifth-order accurate Runge-Kutta pair of Bogacki and Shampine gives much greater accuracy at a significantly reduced computational cost. Specifically, we demonstrate speedups of 2× to 10× for the same accuracy. Numerical tests (including the Taylor-Green vortex, Rayleigh-Taylor instability, and homogeneous isotropic turbulence) confirm the reliability and efficiency of the method. We also show that adaptive time stepping provides a significant computational advantage for some problems (like the development of a Rayleigh-Taylor instability) without compromising accuracy. 相似文献
7.
介绍了一种条带束流位置监测器(BPM)的设计与仿真方法。在国家同步辐射实验室"太赫兹近场高通量材料物性测试系统"工程项目中,针对波荡器出口处真空室非正交对称性的问题,设计了矩形真空室和跑道形真空室下的两种非正交对称性条带BPM,并与传统的圆形真空室下条带BPM进行对比。基于边界元法,利用MATLAB软件分别对三种真空室下的条带BPM进行建模和仿真。仿真结果表明:相对于传统的圆形真空室下条带BPM,矩形和跑道形真空室下条带BPM灵敏度提高了30%,阻抗匹配误差相对降低了20%,束流位置拟合误差降低了80%。考虑加工精度,矩形真空室下的条带BPM更适用于该工程。 相似文献
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Renny Mathew Karolina A. Uchman Lydia Gkoura Chris J. Pickard Maria Baias 《Magnetic resonance in chemistry : MRC》2020,58(11):1018-1025
A combined experimental and computational approach was used to distinguish between different polymorphs of the pharmaceutical drug aspirin. This method involves the use of ab initio random structure searching (AIRSS), a density functional theory (DFT)-based crystal structure prediction method for the high-accuracy prediction of polymorphic structures, with DFT calculations of nuclear magnetic resonance (NMR) parameters and solid-state NMR experiments at natural abundance. AIRSS was used to predict the crystal structures of form-I and form-II of aspirin. The root-mean-square deviation between experimental and calculated 1H chemical shifts was used to identify form-I as the polymorph present in the experimental sample, the selection being successful despite the large similarities between the molecular environments in the crystals of the two polymorphs. 相似文献
10.
Software aging is a phenomenon referring to the performance degradation of a long-running software system. This phenomenon is an accumulative process during execution, which will gradually lead the system from a normal state to a failure-prone state. It is a crucial challenge for system reliability to predict the Aging-Related Failures (ARFs) accurately. In this paper, permutation entropy (PE) is modified to Multidimensional Multi-scale Permutation Entropy (MMPE) as a novel aging indicator to detect performance anomalies, since MMPE is sensitive to dynamic state changes. An experiment is set on the distributed database system Voldemort, and MMPE is calculated based on the collected performance metrics during execution. Finally, based on MMPE, a failure prediction model using the machine learning method to reveal the anomalies is presented, which can predict failures with high accuracy. 相似文献