Early Identification of the Jiangdingya Landslide of Zhouqu Based on SBAS-InSAR Technology   总被引：1，自引：1，他引：0  

YU Haihu  CAI Guolin  GAN Quan  SHEN Dong 《中国地震研究》2020,34(4):510-522

SBAS-InSAR technology is characterized by the advantages of reducing the influence of terrain-simulation error, time-space decorrelation, atmospheric error, thereby improving the reliability of surface-deformation monitoring. This paper studies the early landslide identification method based on SBAS-InSAR technology. Selecting the Jiangdingya landslide area in Zhouqu County, Gansu Province as the research area, 84 ascending-orbit Sentinel-1A SAR images from 2015 to 2019 are collected. In addition, using SBAS-InSAR technology, the rate and time-series results of surface deformation of the landslide area in Jiangdingya during this period are extracted, and potential landslides are identified. The results show that the early landslide identification method based on SBAS-InSAR technology is highly feasible and is a better tool for identifying potential landslides in large areas.  相似文献   

两株南极枝孢霉属真菌Cladosporium sp.NJF4和NJF6的次级代谢产物研究          下载免费PDF全文

常俊男  田晓清  樊成奇  黄金昌  陆亚男  韩清华 《极地研究》2020,32(1):60-67

南极因其独特的自然环境成为潜在、重要的微生物资源库,是产生新型生物活性物质和先导化合物菌株的潜在种源地,南极微生物正在成为创新药物研究新的重要资源。虽然近年来对南极微生物次级代谢产物的研究逐渐增加,但与温带和热带微生物研究相比仍处于初级阶段。对从南极普里兹湾海洋沉积物中获得的两株枝孢霉属真菌Cladosporium sp. NJF4和NJF6进行次级代谢产物分离及结构鉴定,获得20个化合物。化合物结构类型包括甾醇(1)、倍半萜类(7—8)、生物碱类(9—14)、二酮哌嗪(2—5、15—17)、芳香酸(6、18—19)等,其中倍半萜类(7—8)为首次从枝孢霉属真菌中分离得到,以上研究将为丰富南极微生物次级代谢产物库奠定一定的研究基础。  相似文献   

Application of PSO-LIBSVM in Recognition of Potassium Salt Deposits     

Fuqiang Yang  Kegui Chen  Changbing Huang  Yuanyuan Chen  Jin Li  Xiaolin Ma 《地球科学进展》2019,34(7):757-764

The shortage of potassium salt seriously restricts the development of China's agriculture. Increasing the exploration and development of potash will help improve the self-sufficiency of potassium in China. With rich potassium salt resources, Sichuan basin is one of the most important research areas for potash exploration and development in China. Polyhalite is an important solid potassium salt mineral in Sichuan basin, often intercalated in rock minerals such as anhydrite, rock salt and dolomite. Aiming at the problem that conventional log interpretation methods are difficult to accurately identify polyhalites, this paper proposed a new Support Vector Machine (SVM) recognition method based on Particle Swarm Optimization (PSO) to classify polyhalites in Sichuan basin. Based on particle swarm optimization and support vector machine theory, combined with logging interpretation theory, the effective data sensitive to polyhalite logging response were selected as input samples to generate training sets and test sets randomly. The Radial Basis Function (RBF) parameters were optimized by particle swarm optimization, and the classification and prediction model of polyhalite was established. Compared with mud logging results, the recognition accuracy of SVM model based on particle swarm optimization reached 97.5758%, which is obviously better than that of SVM model optimized by cross validation method in recognition accuracy and speed. The results show that the model has broad application prospects in potash exploration in Sichuan basin.  相似文献   

基于钻进状态监测的智能工况识别          下载免费PDF全文

范海鹏  吴敏  曹卫华  赖旭芝  陈略峰  陆承达 《探矿工程》2020,47(4):106-113

钻进过程状态监测旨在实时描述钻进工况，判断运行性能优劣程度进行非优追溯，及时指导司钻人员调整作业操作,保证钻进过程安全、高效、稳定开展。钻进工况是钻进系统运行状态的反映，因此开展面向状态监测技术的钻进工况识别研究具有重要的理论和应用价值。本文针对钻进工况识别问题，基于状态监测数据，建立基于支持向量机的钻进工况识别模型，对钻进工况进行识别。综合工况识别结果，对钻进效率进行评估，并对影响钻进效率的因素进行讨论，寻找提升钻进效率的手段。最后，采用钻进现场实钻数据进行仿真实验,验证所提方法的可行性和有效性。  相似文献   

基于AUKF的框架结构离线模型更新混合试验方法     

陈凡  郭玉荣 《地震工程与工程振动》2020,(1):162-170

模型更新混合试验在传统混合试验方法的基础上更新与试验构件具有相同恢复力特性的构件,扩展了混合试验方法的应用范围。本文旨在提高模型更新混合试验的精度,降低试验的成本并简化模型更新混合试验方法的流程。自适应UKF(AUKF)算法在传统UKF的基础上加入方差自适应模块,能够减轻初始参数设定对参数识别结果的影响,本文基于AUKF提出一种模型更新混合试验方法。对以Bouc-Wen为恢复力模型的防屈曲约束支撑(BRB)进行低周反复加载虚拟试验,通过Matlab编制AUKF算法程序进行参数识别,验证了AUKF算法的高效准确性。对一榀8层4跨带BRB的钢框架进行混合试验数值仿真,结果表明离线模型更新试验结果较在线模型更新更接近真实结果,且简化了试验流程。  相似文献   

Groundwater contaminant source identification based on iterative local update ensemble smoother          下载免费PDF全文

YANG Ai-lin  JIANG Si-min  LIU Jin-bing  JIANG Qian-yun  ZHOU Ting  ZHANG Wen 《地下水科学与工程》2020,8(1):1-9

Identification of the location and intensity of groundwater pollution source contributes to the effect of pollution remediation, and is called groundwater contaminant source identifcation. This is a kind of typical groundwater inverse problem, and the solution is usually ill-posed. Especially considering the spatial variability of hydraulic conductivity field, the identification process is more challenging. In this paper, the solution framework of groundwater contaminant source identification is composed with groundwater pollutant transport model (MT3DMS) and a data assimilation method (Iterative local update ensemble smoother, ILUES). In addition, Karhunen-Loève expansion technique is adopted as a PCA method to realize dimension reduction. In practical problems, the geostatistical method is usually used to characterize the hydraulic conductivity feld, and only the contaminant source information is inversely calculated in the identifcation process. In this study, the identification of contaminant source information under Kriging K-field is compared with simultaneous identification of source information and K-field. The results indicate that it is necessary to carry out simultaneous identification under heterogeneous site, and ILUES has good performance in solving high-dimensional parameter inversion problems.  相似文献   

新矿物与新矿物研究创新探索     

李国武 《地学前缘》2020,27(5):1-9

作为矿物学的重要基础研究方向之一,新矿物的发现及其晶体结构、晶体化学的研究始终备受各发达国家的一贯重视。新矿物的研究和发现及其成果具有国际性,在一定程度上反映了国家在该领域以及整体科技水平和对科学发现的贡献。笔者近年来参与了对若干存疑矿物进行的精细晶体结构与晶体化学研究和矿物学研究,从2005年至今参与发现的23种新矿物均获得国际矿物学协会新矿物及分类命名委员会(IMA-CNMNC)所批准。这些新矿物的获批得益于成功地获取了成分数据、衍射数据和晶体结构的阐明。本文就新矿物的认定规则、申报内容和数据、分类命名、研究内容及工作方法等进行综述,在此抛砖引玉,希望通过交流促进我国新矿物研究领域的发展。  相似文献   

Enhancement of backtracking search algorithm for identifying soil parameters     

Yin-Fu Jin  Zhen-Yu Yin 《国际地质力学数值与分析法杂志》2020,44(9):1239-1261

In this paper, an enhanced backtracking search algorithm (so-called MBSA-LS) for parameter identification is proposed with two modifications: (a) modifying the mutation of original backtracking search algorithm (BSA) considering the contribution of current best individual for accelerating convergence speed and (b) novelly incorporating an efficient differential evolution (DE) as local search for improving the quality of population. The proposed MBSA-LS is first validated with better performance than the original BSA and some other typical state-of-the-art optimization algorithms on a benchmark of soil parameter identification in terms of effectiveness, efficiency, and robustness. Then, the efficiency of the MBSA-LS is further illustrated by two representative cases: identifying soil parameters from both laboratory tests and field measurements. All comparisons demonstrate that the proposed MBSA-LS algorithm can give accurate results in a short time. Finally, to conveniently solve the problems of parameter identification, a practical tool ErosOpt for parameter identification is developed by integrating the proposed MBSA-LS and some other efficient algorithms for readers to conduct the parameter identification using optimisation algorithms.  相似文献   

中国沿海常见蜑螺科贝类的DNA条形码   总被引：1，自引：0，他引：1  

张晓洁  孔令锋  李琪 《海洋与湖沼》2018,49(3):614-623

DNA条形码不仅为物种鉴定提供了有效方法,而且也有助于分类学和生物多样性研究。本研究旨在探讨将COI和16S rRNA基因序列应用于中国沿海蜑螺科贝类物种鉴定的可行性,获得了该科3属7种贝类61个个体的COI和16S rRNA基因序列。基于COI基因序列的种内遗传距离为0.00—1.29%,平均为0.67%;属内种间遗传距离为4.62%—19.25%,平均为13.02%;基于16S rRNA基因序列的种内遗传距离为0.00%—0.48%,平均为0.23%;属内种间遗传距离为2.47%—8.48%,平均为6.37%。两种基因序列在所研究的蜑螺中,种内遗传差异均小于种间遗传差异,存在明显的条形码间隙,所有物种在系统发生树上都表现为独立的单系群。结果表明,线粒体COI和16S rRNA基因序列可以作为DNA条形码标准基因对蜑螺科贝类进行有效地物种鉴定。  相似文献   

Discussion of user-defined parameters for recursive subspace identification: Application to seismic response of building structures     

Shieh-Kung Huang  Jun-Da Chen  Kenneth J. Loh  Chin-Hsiung Loh 《地震工程与结构动力学》2020,49(15):1738-1757

Structural damage assessment under external loading, such as earthquake excitation, is an important issue in structural safety evaluation. In this regard, an appropriate data analysis and system identification technique is required to interpret the measured data and to identify the state of the structure. Generally, the recursive system identification algorithm is used. In this study, the recursive subspace identification (RSI) algorithm based on the matrix inversion lemma algorithm with oblique projection technique (RSI-Inversion-Oblique) is applied to investigate the time-varying dynamic characteristics. The user-defined parameters used in the RSI-Inversion-Oblique technique are carefully discussed, which include the size of the data Hankel matrix (i), model order to extract the physical modes, and forgetting factor (FF) to detect the time-varying system modal frequencies. Response data from the Northridge earthquake from the Sherman Oaks building (CSMIP) is used as an example to examine a systematic method to determine the suitable user-defined parameters in RSI. It is concluded that the number of rows in the data Hankel matrix significantly influences the identification of the time-varying fundamental modal frequency of the structure. An algorithmic model order selection method using the eigenvalue distribution of RSI-Inversion can detect the system modal frequencies at each appending data window without causing any abnormality.  相似文献