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| 1 | A hybrid inversion method of damped least squares with simulated annealing used for Rayleigh wave dispersion curve inversion显示文摘Surface wave methods are becoming increasingly popular in many geotechnical applications and in earthquake seismology due to their noninvasive characteristics.Inverse surface wave dispersion curves are a crucial step in most surface wave methods.Many inversion methods have been applied to surface wave dispersion curve inversion,including linearized inversion and nonlinearized inversion methods.In this study,a hybrid inversion method of Damped Least Squares(DLS) with Very Fast Simulated Annealing(VFSA) is developed for multi-mode Rayleigh wave dispersion curve inversion.Both synthetic and in situ fi eld data were used to verify the validity of the proposed method.The results show that the proposed method is superior to the conventional VFSA method in aiming at global minimum,especially when parameter searching space is adjacent to real values of the parameters.The advantage of the new method is that it retains both the merits of VFSA for global search and DLS for local search.At high temperatures,the global search dominates the runs,while at a low temperatures,the local search dominates the runs.Thus,at low temperatures,the proposed method can almost directly approach the actual model. | Lu Jianqi Li Shanyou Li Wei Tang Lihua | 2014 | Earthquake Engineering and Engineering Vibration2014，13，1： | 4 |
| 2 | Disaggregation of land surface temperature over a heterogeneous urban and surrounding suburban area: a case study in Shanghai, China显示文摘 | Shanyou Zhu Huade Guan AndrewC. Millington Guixin Zhang | 2013 | International Journal of Remote Sensing2013，，5： | 1 |
| 3 | Monitoring Spatio-temporal Variance of an Extreme Heat Event Using Multiple-source Remote Sensing Data显示文摘Extreme heat events have serious effects on human daily life. Accurately capturing the dynamic variance of extreme high-temperature distributions in a timely manner is the basis for analyzing the potential impacts of extreme heat, thereby informing risk prevention strategies. This paper demonstrates the potential application of multiple source remote sensing data in mapping and monitoring the extreme heat events that occurred on Aug. 8, 2013 in Jiangsu Province, China. In combination with MODIS products, the thermal sharpening(Ts HARP) method and a binary linear model are compared to downscale the original daytime FengY un 2 F(FY-2 F) land surface temperature(LST) imagery, with a temporal resolution of 60 min, from 5 km to 1 km. Using the meteorological measurement data from Nanjing station as the reference, the research then estimates the instantaneous air temperature by using an iterative computation based on the Surface Energy Balance Algorithm for Land(SEBAL), which is used to analyze the spatio-temporal air temperature variance. The results show that the root mean square error(RMSE) of the LST downscaled from the binary linear model is 1.30℃ compared to the synchronous MODIS LST, and on this basis the estimated air temperature has the RMSE of 1.78℃. The spatial and temporal distribution of air temperature variance at each geographical location from 06:30 to 18:30 can be accurately determined, and indicates that the high temperature gradually increases and expands from the city center. For the spatial distribution, the air temperature and the defined scorching temperature proportion index increase from northern to middle, to southern part of Jiangsu, and are slightly lower in the eastern area near the Yellow Sea. In terms of temporal characteristics, the percentage of area with air temperature above 37℃ in each city increase with time after 10:30 and reach the peak value at 14:30 or 15:30. Then, they decrease gradually, and the rising and falling trends become smaller from the southern cities to the northern regions. Moreover, there is a distinct positive relationship between the percentage of area above 37℃ and the population density. The above results show that the spatio-temporal distributions of heat waves and their influencing factors can be determined by combining multiple sources of remotely sensed image data. | ZHU Shanyou LIU Yi HUA Junwei ZHANG Guixin ZHOU Yang XIANG Jiamin | 2018 | Chinese Geographical Science2018，28，5： | 1 |
| 4 | An Indendation Model for theNorth and South China Collision and the Developmentof the Tan - Lu and Honam Fault System,EasternAsia显示文摘 | Yin An Nie Shanyou | 1993 | Tectonics1993，12，： | 1 |
| 5 | Continuous prediction method of earthquake early warning magnitude for high-speed railway based on support vector machine显示文摘Purpose–Using the strong motion data ofK-net in Japan,the continuous magnitude prediction method based on support vector machine(SVM)was studied.Design/methodology/approach–In the range of 0.5–10.0 s after the P-wave arrival,the prediction time window was established at an interval of 0.5 s.12 P-wave characteristic parameters were selected as the model input parameters to construct the earthquake early warning(EEW)magnitude prediction model(SVM-HRM)for high-speed railway based on SVM.Findings–The magnitude prediction results of the SVM-HRM model were compared with the traditional magnitude prediction model and the high-speed railway EEW current norm.Results show that at the 3.0 s time window,themagnitude prediction error of the SVM-HRMmodel is obviously smaller than that of the traditionalτc method and Pd method.The overestimation of small earthquakes is obviously improved,and the construction of the model is not affected by epicenter distance,so it has generalization performance.For earthquake events with themagnitude range of 3–5,the single station realization rate of the SVM-HRMmodel reaches 95%at 0.5 s after the arrival of P-wave,which is better than the first alarm realization rate norm required by“The TestMethod of EEW andMonitoring Systemfor High-Speed Railway.”For earthquake eventswithmagnitudes ranging from3 to 5,5 to 7 and 7 to 8,the single station realization rate of the SVM-HRM model is at 0.5 s,1.5 s and 0.5 s after the P-wave arrival,respectively,which is better than the realization rate norm of multiple stations.Originality/value–At the latest,1.5 s after the P-wave arrival,the SVM-HRM model can issue the first earthquake alarm that meets the norm of magnitude prediction realization rate,which meets the accuracy and continuity requirements of high-speed railway EEW magnitude prediction. | Jindong Song Jingbao Zhu Shanyou Li | 2022 | Railway Sciences2022，1，2： | 0 |
| 6 | Random Forest-Based Snow Cover Mapping in China Using Fengyun-3B VIRR Data显示文摘Currently,there is variability in the spectral band thresholds for snow cover recognition using remote sensing in different regions and for complex terrains.Using Fengyun-3B Visible and Infra-Red Radiometer(FY-3B VIRR)satellite data,we applied random forest(RF)methodology and selected 13 feature variables to obtain snow cover.A training set was generated,containing approximately 1 million snow and nonsnow samples obtained in China from the snow monitoring reports issued by the National Satellite Meteorological Centre and four snow cover products from the Interactive Multi-sensor Snow and Ice Mapping System(IMS),the FY-3B Multi-Sensor Synergy(MULSS),the Moderate Resolution Imaging Spectroradiometer(MODIS)snow cover product(MYD10A1),and the National Cryosphere Desert Data Center(NCDC).This training set contained many different samples of cloud types and snow under forest cover to help effectively distinguish snow and clouds and improve the recognition rate of snow under forest cover.Then,two RF snow cover recognition models were constructed for the snow and nonsnow seasons and they were used to conduct daily snow cover recognition in China from 2011 to 2020.The results show that the RF models constructed based on FY-3B VIRR data have good recognition performance for shallow snow,understory snow,and snow on the Qinghai–Tibetan Plateau.The recognition accuracy against weather stations and the spatial consistency with the IMS product are better than the MULSS,MYD10A1,and NCDC products.The overall accuracy of the RF product is 90.6%,and the recall rate is 93.8%.The omission and commission errors are 6.2%and11.1%,respectively.Unlike other existing snow cover algorithms,the established RF model skips the complicated atmospheric correction and cloud identification processes and does not involve external auxiliary data;thus,it is more easily popularized and operationally applicable to generating long-time series snow cover products. | Yuchen XIE Yonghong LIU Yeping ZHANG Fuzhong WENG Shanyou ZHU Zhaojun ZHENG Shihao TANG | 2023 | Journal of Meteorological Research2023，37，5： | 0 |
| 7 | Real-time prediction of earthquake potential damage:A case study for the January 8,2022 M_(S) 6.9 Menyuan earthquake in Qinghai,China显示文摘It is critical to determine whether a site has potential damage in real-time after an earthquake occurs,which is a challenge in earthquake disaster reduction.Here,we propose a real-time Earthquake Potential Damage predictor(EPDor)based on predicting peak ground velocities(PGVs)of sites.The EPDor is composed of three parts:(1)predicting the magnitude of an earthquake and PGVs of triggered stations based on the machine learning prediction models;(2)predicting the PGVs at distant sites based on the empirical ground motion prediction equation;(3)generating the PGV map through predicting the PGV of each grid point based on an interpolation process of weighted average based on the predicted values in(1)and(2).We apply the EPDor to the 2022 M_(S) 6.9 Menyuan earthquake in Qinghai Province,China to predict its potential damage.Within the initial few seconds after the first station is triggered,the EPDor can determine directly whether there is potential damage for some sites to a certain degree.Hence,we infer that the EPDor has potential application for future earthquakes.Meanwhile,it also has potential in Chinese earthquake early warning system. | Jindong Song Jingbao Zhu Yongxiang Wei Shuilong Li Shanyou Li | 2023 | Earthquake Research Advances2023，3，1： | 0 |
| 8 | STUDY ON STRUCTURE AND PROPERTIES OF 18Si MnCu DUAL PHASE STEEL显示文摘STUDYONSTRUCTUREANDPROPERTIESOF18SiMnCuDUALPHASESTEEL￥YuShenjun;GongFangyue;LiShanyou;WangChunyan;ChenYuru;ChenFumin(TianjinU... | Yu Shenjun Gong Fangyue Li Shanyou Wang Chunyan Chen Yuru Chen Fumin (Tianjin University) Yang Sicong WangShixun (Tianjin First Rolling Mill)(Tianjin Iron and Steel Research Institute) | 1994 | Chinese Journal of Mechanical Engineering1994，7，2： | 0 |
| 9 | Verma Module of U_(q)(B_(2))显示文摘This paper deals with the Verma module of quantum group U_(q)(B_(2)) when q is a root of 1.It estimates how many classes of Verma submodules which are not isomorphic to each other are contained in Verma module.The character of irreducible highest weight module ofU_(q)(B_(2)) has also been given. | ZHOU Shanyou | 1994 | Chinese Physics Letters1994，11，1： | 0 |
| 10 | Synthesis of True Color Images from the Fengyun Advanced Geostationary Radiation Imager显示文摘The production of true color images requires observational data in the red,green,and blue(RGB)bands.The Advanced Geostationary Radiation Imager(AGRI)onboard China’s Fengyun-4(FY-4)series of geostationary satellites only has blue and red bands,and we therefore have to synthesize a green band to produce RGB true color images.We used random forest regression and conditional generative adversarial networks to train the green band model using Himawari-8 Advanced Himawari Imager data.The model was then used to simulate the green channel reflectance of the FY-4 AGRI.A single-scattering radiative transfer model was used to eliminate the contribution of Rayleigh scattering from the atmosphere and a logarithmic enhancement was applied to process the true color image.The conditional generative adversarial network model was better than random forest regression for the green band model in terms of statistical significance(e.g.,a higher determination coefficient,peak signal-to-noise ratio,and structural similarity index).The sharpness of the images was significantly improved after applying a correction for Rayleigh scattering,and the images were able to show natural phenomena more vividly.The AGRI true color images could be used to monitor dust storms,forest fires,typhoons,volcanic eruptions,and other natural events. | Yuchen XIE Xiuzhen HAN Shanyou ZHU | 2021 | Journal of Meteorological Research2021，35，6： | 0 |
| 11 | Spatial Distribution of High-temperature Risk with a Return Period of Different Years in the Yangtze River Delta Urban Agglomeration显示文摘Against the background of global warming,research on the spatial distribution of high-temperature risk is of great significance to effectively prevent the adverse effects of high temperatures.By using air temperature data from 1951 to 2018 measured by meteorological stations located in the Yangtze River Delta urban agglomeration,the daily maximum air temperature distribution is interpolated at a resolution of 1 km based on the local thin disk smooth spline function;the high-temperature threshold for return periods of 5,10,20 and 30 yr are then calculated by using the generalized extreme value method.The yearly average high-temperature intensity and high-temperature days are finally calculated as high-temperature danger factors.Socioeconomic statistical data and remotely sensed image data in 2018 are used as the background data to calculate the spatial distribution of high-temperature vulnerability factors and prevention capacity factors,which are then used to compute the high-temperature risk index during different recurrence periods in the Yangtze River Delta urban agglomerations.The results show that the spatial distribution features of high-temperature risk in different return periods are similar.The high-temperature risk index gradually increases from northeast to southwest and from east coast to inland,which has obvious latitude variation characteristics and a relationship with the comprehensive influence of the underlying surface and urban scale.In terms of time variation,the high-temperature risk index and its spatial distribution difference gradually decreases with increasing return period.In different cities,the high-temperature risk in the central area of the city is generally higher than that in the surrounding suburban areas.Jinhua,Hangzhou of Zhejiang Province and Xuancheng of Anhui Province are the top three cities with high-temperature risk in the study area. | ZHANG Guixin WANG Shisheng ZHU Shanyou XU Yongming | 2022 | Chinese Geographical Science2022，32，6： | 0 |
| 12 | Prospects for the Development and Application of the Earthquake Monitoring Network显示文摘With the rapid development of the economy in China, the seismic network has been changing rapidly, in that the capability of instruments, technological systems and network density are approaching those of developed countries and a large quantity of observation data has been accumulated. How to apply these resources to economic construction and public safety has become an important issue worth studying. In order to improve earthquake prediction and earthquake emergency response, it is suggested in this paper that extracting valuable precursor information, improving earthquake rapid reporting ability and extending rapid intensity reporting function are key issues. Integrating network resources, building unified standards and a multifunction seismic monitoring network are preconditions of establishing a public safety service platform and earthquake observation resources will contribute significantly to the fields of engineering, ocean, meteorology, and environmental protection. Thus, the future directions of the development of the seismic network are exploring monitoring resources, enhancing independent innovation, constructing a technological platform and enlarging the service field. | Jin Xing Li Shanyou Li Zuning Kang Lanchi Li Jun | 2007 | Earthquake Research in China2007，21，2： | 0 |
| 13 | The Action of Structure and Efficiency on Energy Intensity Variation in China- An Empirical Analysis Based on AWD显示文摘 | Yong Zhou Shanyou Kong Guofu Wu | 2008 | Journal of Systems Science and Information2008，6，2： | 0 |
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