The accuracy of historical situation values is required for traditional network security situation prediction(NSSP).There are discrepancies in the correlation and weighting of the various network security elements.To ...The accuracy of historical situation values is required for traditional network security situation prediction(NSSP).There are discrepancies in the correlation and weighting of the various network security elements.To solve these problems,a combined prediction model based on the temporal convolution attention network(TCAN)and bi-directional gate recurrent unit(BiGRU)network is proposed,which is optimized by singular spectrum analysis(SSA)and improved quantum particle swarmoptimization algorithm(IQPSO).This model first decomposes and reconstructs network security situation data into a series of subsequences by SSA to remove the noise from the data.Furthermore,a prediction model of TCAN-BiGRU is established respectively for each subsequence.TCAN uses the TCN to extract features from the network security situation data and the improved channel attention mechanism(CAM)to extract important feature information from TCN.BiGRU learns the before-after status of situation data to extract more feature information from sequences for prediction.Besides,IQPSO is proposed to optimize the hyperparameters of BiGRU.Finally,the prediction results of the subsequence are superimposed to obtain the final predicted value.On the one hand,IQPSO compares with other optimization algorithms in the experiment,whose performance can find the optimum value of the benchmark function many times,showing that IQPSO performs better.On the other hand,the established prediction model compares with the traditional prediction methods through the simulation experiment,whose coefficient of determination is up to 0.999 on both sets,indicating that the combined prediction model established has higher prediction accuracy.展开更多
Well-designed airfoil is very important for high-performance rotor.This paper developed an efficient multi-objective and multi-constraint optimization design system for rotor airfoils based on RANS analysis,and verifi...Well-designed airfoil is very important for high-performance rotor.This paper developed an efficient multi-objective and multi-constraint optimization design system for rotor airfoils based on RANS analysis,and verified the performance of the optimized airfoil.Using CRA09-A as the baseline rotor airfoil,the CRA09-B optimized rotor airfoil was designed successfully.Combined with the foundation of high-precision rotor airfoil stationary test technology,the CRA09-B and CRA09-A rotor airfoils were tested in the S3 MA high-speed wind tunnel of ONERA.In order to correct the aerodynamic data,a single parameter linear wall pressure method is used to consider the tunnel effects.The results indicate that multi-objective and multi-constraint optimization design method developed in this study is reliable,and that CRA09-B optimized airfoil provides better stationary performance than CRA09-A airfoil in terms of maximum lift coefficient and lift-to-drag ratio.展开更多
The Bu→ψM decays are studied with the perturbative QCD approach, where the psion ψ=ψ（2S）, ψ（3770）, ψ（4040） and ψ（4160）, and the light meson M = π, K, ρ and K^＊. The factorizable and non-factorizable ...The Bu→ψM decays are studied with the perturbative QCD approach, where the psion ψ=ψ（2S）, ψ（3770）, ψ（4040） and ψ（4160）, and the light meson M = π, K, ρ and K^＊. The factorizable and non-factorizable contributions, and the S-D wave mixing effects on the psions, are considered in the calculation. With appropriate inputs, the branching ratios for the Bu→ψM decays are generally coincident with the experimental data within errors. However, due to the large theoretical and experimental errors, it is impossible for the moment to give a severe constraint on the S-D wave mixing angles.展开更多
基金This work is supported by the National Science Foundation of China(61806219,61703426,and 61876189)by National Science Foundation of Shaanxi Provence(2021JM-226)by the Young Talent fund of the University,and the Association for Science and Technology in Shaanxi,China(20190108,20220106)by and the Innovation Capability Support Plan of Shaanxi,China(2020KJXX-065).
文摘The accuracy of historical situation values is required for traditional network security situation prediction(NSSP).There are discrepancies in the correlation and weighting of the various network security elements.To solve these problems,a combined prediction model based on the temporal convolution attention network(TCAN)and bi-directional gate recurrent unit(BiGRU)network is proposed,which is optimized by singular spectrum analysis(SSA)and improved quantum particle swarmoptimization algorithm(IQPSO).This model first decomposes and reconstructs network security situation data into a series of subsequences by SSA to remove the noise from the data.Furthermore,a prediction model of TCAN-BiGRU is established respectively for each subsequence.TCAN uses the TCN to extract features from the network security situation data and the improved channel attention mechanism(CAM)to extract important feature information from TCN.BiGRU learns the before-after status of situation data to extract more feature information from sequences for prediction.Besides,IQPSO is proposed to optimize the hyperparameters of BiGRU.Finally,the prediction results of the subsequence are superimposed to obtain the final predicted value.On the one hand,IQPSO compares with other optimization algorithms in the experiment,whose performance can find the optimum value of the benchmark function many times,showing that IQPSO performs better.On the other hand,the established prediction model compares with the traditional prediction methods through the simulation experiment,whose coefficient of determination is up to 0.999 on both sets,indicating that the combined prediction model established has higher prediction accuracy.
基金supported by the National Natural Science Foundation of China(No.11902335)。
文摘Well-designed airfoil is very important for high-performance rotor.This paper developed an efficient multi-objective and multi-constraint optimization design system for rotor airfoils based on RANS analysis,and verified the performance of the optimized airfoil.Using CRA09-A as the baseline rotor airfoil,the CRA09-B optimized rotor airfoil was designed successfully.Combined with the foundation of high-precision rotor airfoil stationary test technology,the CRA09-B and CRA09-A rotor airfoils were tested in the S3 MA high-speed wind tunnel of ONERA.In order to correct the aerodynamic data,a single parameter linear wall pressure method is used to consider the tunnel effects.The results indicate that multi-objective and multi-constraint optimization design method developed in this study is reliable,and that CRA09-B optimized airfoil provides better stationary performance than CRA09-A airfoil in terms of maximum lift coefficient and lift-to-drag ratio.
基金Supported by the National Natural Science Foundation of China(11705047,U1632109,11547014,11475055)Open Research Program of Large Research Infrastructures(2017)Chinese Academy of Sciences
文摘The Bu→ψM decays are studied with the perturbative QCD approach, where the psion ψ=ψ（2S）, ψ（3770）, ψ（4040） and ψ（4160）, and the light meson M = π, K, ρ and K^＊. The factorizable and non-factorizable contributions, and the S-D wave mixing effects on the psions, are considered in the calculation. With appropriate inputs, the branching ratios for the Bu→ψM decays are generally coincident with the experimental data within errors. However, due to the large theoretical and experimental errors, it is impossible for the moment to give a severe constraint on the S-D wave mixing angles.
