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International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Gao Lu Qianqi Dai Jiechen Xia National Key Laboratory of Science and Technology on Test Physics and umerical Mathematics Beijing Institute of Space Long March Vehicle Beijing China Key Laboratory of Advanced Marine Communication and Information Technology Ministry of Industry and Information Technology Harbin Engineering University Harbin China

Electromagnetic countermeasure plays an important role in modern warfare. Cooperative jamming is one of the main means to counter radar network. In order to improve jamming efficiency, a jamming resource allocation algorithm based on artificial bee colony multi-target decomposition is proposed in this paper. The algorithm takes into account the interference effect and cost, and uses the decomposition mechanism to improve the search efficiency. The simulation results show that the allocation solution set obtained by this algorithm has good performance in diversity and spacing.

关键词： Costs Simulation Radar Interference Computational electromagnetics Artificial bee colony algorithm Radar countermeasures

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Effects of Dropsonde Data in Field Campaigns on Forecasts of Tropical Cyclones over the Western North Pacific in 2020 and the Role of CNOP Sensitivity

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Advances in Atmospheric sciences 2023年第5期40卷 791-803页

作者： Xiaohao QIN Wansuo DUAN Pak-Wai CHAN Boyu CHEN Kang-Ning HUANG State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters Nanjing University of Information Science and TechnologyNanjing 210044China Hong Kong Observatory Hong KongChina Weather Forecasting Office National Meteorological CenterChina Meteorological AdministrationBeijing 100081China Research and Development Center Central Weather BureauTaipei 100006China

Valuable dropsonde data were obtained from multiple field campaigns targeting tropical cyclones,namely Higos,Nangka,Saudel,and Atsani,over the western North Pacific by the Hong Kong Observatory and Taiwan Central Weather Bureau in *** conditional nonlinear optimal perturbation(CNOP)method has been utilized in real-time to identify the sensitive regions for targeting observations adhering to the procedure of real-time field campaigns for the first *** observing system experiments were conducted to evaluate the effect of dropsonde data and CNOP sensitivity on TC forecasts in terms of track and intensity,using the Weather Research and Forecasting *** is shown that the impact of assimilating all dropsonde data on both track and intensity forecasts is ***,assimilation using only the dropsonde data inside the sensitive regions displays unanimously positive effects on both the track and intensity forecast,either of which obtains comparable benefits to or greatly reduces deterioration of the skill when assimilating all dropsonde ***,these results encourage us to further carry out targeting observations for the forecast of tropical cyclones according to CNOP sensitivity.

关键词： tropical cyclones targeting observation field campaign CNOP sensitivity dropsonde intensity forecasts

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Intelligent Assignment Strategy for Multi-Target Adversarial Interception

Intelligent Assignment Strategy for Multi-Target Adversarial...

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Chinese Automation Congress (CAC)

作者： Yang Yu Yizhong Fang Han Wu Tuo Han Qinglei Hu School of Automation Science and Electrical Engineering Beihang University Beijing China National Key Laboratory of Science and Technology on Test Physics & Numerical Mathematics Beijing Institute of Space Long March Vehicle Beijing China School of Aeronautic Science and Engineering Beihang University Beijing China Beihang Hangzhou Innovation Institute (Yuhang) Hangzhou China

The multi-missile confront multi-target is a classic target allocation issue in the combat scenario of multiple missiles intercepting multiple maneuvering targets. Traditional algorithms lack environmental assessment model, train quality, and indicator function in the adversarial environment. To this end, this paper aims to propose an intelligent assignment strategy which contains indicator function and evaluation model. Then, an indicator function and an evaluation model considering the miss distance, threat situation, and the number of specified interception targets are introduced into the reinforcement learning algorithm. The local and global reward functions are introduced to improve the training convergence and efficiency in the multi-missile multi-target confrontation scenario. Finally, simulation results are designed to check on advantage of intelligent allocation strategy.

关键词： Training Missiles Analytical models Automation Simulation Reinforcement learning Resource management

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Comparison of Nonlinear Local Lyapunov Vectors with Bred Vectors, Random Perturbations and Ensemble Transform Kalman Filter Strategies in a Barotropic Model

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Advances in Atmospheric sciences 2016年第9期33卷 1036-1046页

作者： Jie FENG Ruiqiang DING Jianping LI Deqiang LIU State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029 College of Earth Science University of Chinese Academy of SciencesBeijing 100049 Global Systems Division Earth System Research Laboratory/Oceanic and Atmospheric Research/National Oceanic and Atmospheric AdministrationBoulderCO80305USA Plateau Atmosphere and Environment Key Laboratory of Sichuan Province Chengdu University of Information TechnologyChengdu 610225 College of Global Change and Earth System Sciences Beijing Normal UniversityBeijing 100875 Joint Center for Global Change Studies Beijing 100875 Fujian Meteorological Observatory Fuzhou 350001

The breeding method has been widely used to generate ensemble perturbations in ensemble forecasting due to its simple concept and low computational cost. This method produces the fastest growing perturbation modes to catch the growing components in analysis errors. However, the bred vectors （BVs） are evolved on the same dynamical flow, which may increase the dependence of perturbations. In contrast, the nonlinear local Lyapunov vector （NLLV） scheme generates flow-dependent perturbations as in the breeding method, but regularly conducts the Gram-Schmidt reorthonormalization processes on the perturbations. The resulting NLLVs span the fast-growing perturbation subspace efficiently, and thus may grasp more com- ponents in analysis errors than the BVs. In this paper, the NLLVs are employed to generate initial ensemble perturbations in a barotropic quasi-geostrophic model. The performances of the ensemble forecasts of the NLLV method are systematically compared to those of the random pertur- bation （RP） technique, and the BV method, as well as its improved version--the ensemble transform Kalman filter （ETKF） method. The results demonstrate that the RP technique has the worst performance in ensemble forecasts, which indicates the importance of a flow-dependent initialization scheme. The ensemble perturbation subspaces of the NLLV and ETKF methods are preliminarily shown to catch similar components of analysis errors, which exceed that of the BVs. However, the NLLV scheme demonstrates slightly higher ensemble forecast skill than the ETKF scheme. In addition, the NLLV scheme involves a significantly simpler algorithm and less computation time than the ETKF method, and both demonstrate better ensemble forecast skill than the BV scheme.

关键词： ensemble forecasting bred vector nonlinear local Lyapunov vector ensemble transform Kalman filter

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Perturbation Estimated Incremental Guidance for Exo-Atmospheric Interception

Perturbation Estimated Incremental Guidance for Exo-Atmosphe...

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Chinese Automation Congress (CAC)

作者： Yuting Lu Peng Liu Tuo Han Qinglei Hu School of Automation Science and Electrical Engineering Beihang University Beijing China National Key Laboratory of Science and Technology on Test Physics & Numerical Mathematics Beijing Institute of Space Long March Vehicle Beijing China School of Aeronautic Science and Engineering Beihang University Beijing China Beihang Hangzhou Innovation Institute (Yuhang) Hangzhou China

In order to meet the requirement of accurate intercept against the increased target maneuverability and external disturbance, a second-order inertial delay based incremental guidance law (IDIASMG) is proposed for an exo-atmospheric interceptor. Specifically, a three-dimensional guidance model is transformed into an incremental version. As a guidance design benchmark, a conventional sliding mode guidance law (SMG) is presented, and a sliding mode incremental guidance law (ISMG) is designed with gain adaptation. Moreover, a second-order inertial delay filter is utilized to estimate and compensate guidance perturbation including the target maneuver, system uncertainty, and external disturbance. Theoretical analysis shows that the incremental guidance requires smaller gains to ensure smaller system residual than the conventional SMG. Extensive numerical simulations validate the effectiveness and robustness of IDIASMG.

关键词： Solid modeling Uncertainty Adaptive systems Upper bound Navigation Perturbation methods numerical simulation

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A finite point method based on directional derivatives for diffusion equation

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World Academy of science, Engineering and technology 2011年 81卷 211-216页

作者： Lv, Guixia Shen, Longjun National Key Laboratory of Science and Technology on Computational Physics Institute of Applied Physics and Computational Mathematics P. O. Box 8009-26 Beijing 100088 China

This paper presents a finite point method based on directional derivatives for diffusion equation on 2D scattered points. To discretize the diffusion operator at a given point, a six-point stencil is derived by employing explicit numerical formulae of directional derivatives, namely, for the point under consideration, only five neighbor points are involved, the number of which is the smallest for discretizing diffusion operator with first-order accuracy. A method for selecting neighbor point set is proposed, which satisfies the solvability condition of numerical derivatives. Some numerical examples are performed to show the good performance of the proposed method.

关键词： numerical methods

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Iteration acceleration for nonlinear coupled parabolic-hyperbolic system

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World Academy of science, Engineering and technology 2011年 81卷 624-629页

作者： Cui, Xia Yuan, Guang-Wei Yue, Jing-Yan National Key Laboratory of Science and Technology on Computational Physics Institute of Applied Physics and Computational Mathematics P. O. Box 8009-26 Beijing 100088 China

A Picard-Newton iteration method is studied to accelerate the numerical solution procedure of a class of two-dimensional nonlinear coupled parabolic-hyperbolic system. The Picard-Newton iteration is designed by adding higher-order terms of small quantity to an existing Picard iteration. The discrete functional analysis and inductive hypothesis reasoning techniques are used to overcome difficulties coming from nonlinearity and coupling, and theoretical analysis is made for the convergence and approximation properties of the iteration scheme. The Picard-Newton iteration has a quadratic convergent ratio, and its solution has second order spatial approximation and first order temporal approximation to the exact solution of the original problem. numerical tests verify the results of the theoretical analysis, and show the Picard-Newton iteration is more efficient than the Picard iteration.

关键词： Convergence of numerical methods

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The first 5-year Clean Air Action did increase the blue days in winter over Beijing-Tianjin-Hebei

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science Bulletin 2022年第8期67卷 774-776页

作者： Su Wang Gang Huang Tie Dai Kaiming Hu State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Laboratory for Regional Oceanography and Numerical Modeling Pilot National Laboratory for Marine Science and Technology(Qingdao)Qingdao 266237China University of Chinese Academy of Sciences Beijing 100049China Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disaster of Ministry of Education Nanjing University of Information Science and TechnologyNanjing 210044China Center for Monsoon System Research Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China

China has made great efforts to mitigate its long-standing environmental problem in recent *** China,during the first 5-year Clean Air Action(2013–2017),remarkable reductions in primary pollutants such as SO_(2) and ... 详细信息

关键词：大气污染防治 Clean Tianjin

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Seamless Prediction in China: A Review

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Advances in Atmospheric sciences 2023年第8期40卷 1501-1520页

作者： Hong-Li REN Qing BAO Chenguang ZHOU Jie WU Li GAO Lin WANG Jieru MA Yao TANG Yangke LIU Yujun WANG Zuosen ZHAO State Key Laboratory of Severe Weather and Institute of Tibetan Plateau MeteorologyChinese Academy of Meteorological SciencesBeijing 100081China Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD) Nanjing University of Information Science and TechnologyNanjing 210044China State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Department of Atmospheric Science School of Environmental StudiesChina University of GeosciencesWuhan 430074China China Meteorological Administration Key Laboratory for Climate Prediction Studies National Climate CenterChina Meteorological AdministrationBeijing 100081China Ensemble Forecasting Division CMA Earth System Modeling and Prediction Center(CEMC)Beijing 100081China School of Atmospheric Sciences Chengdu University of Information TechnologyChengdu 610225China

Seamless prediction is a weather-climate integrated prediction covering multiple time scales that include days,weeks,months,seasons,years,and *** prediction can provide different industries with information such as weather conditions and climate variations from the next few days to years,which have important impacts on economic and social development and important reference value for short-,medium-and long-term decision-making and planning of the ***,seamless prediction has received widespread attention from the international scientific community *** Chinese scientists have also carried out relevant research,this paper reviews the research in China on developments and applications of seamless prediction methods and prediction systems in recent *** them,the main progress of seamless prediction methods studies is reviewed from four aspects:short-and medium-range weather forecasting,subseasonal-to-seasonal,seasonal-to-interannual,and decadal climate *** terms of development and application of seamless prediction systems,the main achievements made by meteorological operational departments,scientific institutes,and universities in China in recent years are ***,some of the issues in seamless prediction that need further study are discussed.

关键词： seamless prediction weather-climate integrated prediction prediction system

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Deep learning to evaluate seismic-induced soil liquefaction and modified transfer learning between various data sources

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Underground Space 2025年

作者： Hongwei Guo Chao Zhang Hongyuan Fang Timon Rabczuk Xiaoying Zhuang Department of Geotechnical Engineering College of Civil Engineering Tongji University Shanghai 200092 China Key Laboratory of Urban Security and Disaster Engineering Ministry of Education Beijing University of Technology Beijing 100124 China School of Water Conservancy and Transportation/Yellow River Laboratory/Underground Engineering Research Institute Zhengzhou University Zhengzhou 450001 China National Local Joint Engineering Laboratory of Major Infrastructure Testing and Rehabilitation Technology Zhengzhou 450001 China Collaborative Innovation Center for Disaster Prevention and Control of Underground Engineering Jointly Built by Provinces and Ministries Zhengzhou 450001 China Institute of Structural Mechanics Bauhaus University Weimar Weimar 99425 Germany Chair of Computational Science and Simulation Technology Faculty of Mathematics and Physics Leibniz University Hannover Hannover 30167 Germany

Soil liquefaction assessment remains a crucial and complex challenge in seismic geotechnical engineering due to various liquefaction records and limited information, which entails a more generalized off-the-shelf model that can achieve favourable performance on different data sources. In this work, a deep learning model is built and investigated on the soil liquefaction prediction and a modified transfer learning scheme between different data sources is presented. Various datasets, including shear wave velocity-based, CPT-based, SPT-based, and real cases, are collected and utilized to verify the effectiveness and accuracy of the proposed model. Because different data sources in soil liquefaction generally share several geotechnical and mechanical parameters, we work to combine model prior information, feature mapping and data reconstruction in transfer learning models to tackle multi-source domain adaption, which can be further applied to other predictive analysis and facilitate online learning models in geotechnical engineering. Also, the deep learning model is compared with several classical machine learning and ensemble learning models and the modified transfer learning model is formulated by comparing different feature transformation techniques integrated with various feature-based and instance-based transfer learning methods. The accuracy and effectiveness of the deep learning and modified transfer learning models have been validated in the numerical study.

关键词： Liquefaction Prediction Deep learning Ensemble methods Transfer learning Feature-based Instance-based Source data Target data Deep autoencoder Variational autoencoder

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