新疆测震台网记录的远距离工业爆破分析

对新疆测震台网数字化记录中的宁夏ML4．4爆破记录进行了分析,新疆台网大部分台站都能记录到上千公里ML4.0以上的工业爆破。又对新疆巴里坤地震台记录的约1200km的宁夏ML3．8、内蒙ML4．2地震和宁夏ML4．4的工业爆破记录进行了分析,发现近距离爆破记录的特征大部分可以在远距离爆破中找到。     

Optimal design of structures for earthquake loads by a hybrid RBF-BPSO method

The optimal seismic design of structures requires that time history analyses （THA） be carried out repeatedly. This makes the optimal design process inefficient, in particular, if an evolutionary algorithm is used. To reduce the overall time required for structural optimization, two artificial intelligence strategies are employed. In the first strategy, radial basis function （RBF） neural networks are used to predict the time history responses of structures in the optimization flow. In the second strategy, a binary particle swarm optimization （BPSO） is used to find the optimum design. Combining the RBF and BPSO, a hybrid RBF-BPSO optimization method is proposed in this paper, which achieves fast optimization with high computational performance. Two examples are presented and compared to determine the optimal weight of structures under earthquake loadings using both exact and approximate analyses. The numerical results demonstrate the computational advantages and effectiveness of the proposed hybrid RBF-BPSO optimization method for the seismic design of structures.     

龙滩水电工程数字遥测地震台网技术系统

介绍了龙滩水电站数字遥测地震台网工程技术方案及主要仪器设备选型,通过实际震例检验了台网的监测能力。台网的运行情况表明,台网技术系统先进,设备运行稳定可靠,对监测龙滩库区及附近地震发挥了重要作用。     

基于改进的BP神经网络构建区域精密对流层延迟模型

利用神经网络算法挖掘海量数据的规律已成为科技发展的一种趋势,本文针对卫星信号的天顶对流层延迟进行建模.对流层延迟是影响卫星定位精度的重要因素之一,建立精密区域对流层模型对高精度定位有着重要的意义.对区域测站对流层延迟数据的分析,考虑到实时建模中传统BP（Back Propagation）神经网络计算量大,易出现"过拟合"现象、不稳定等因素,通过改进的BP神经网络建立了区域精密对流层模型.详细介绍了新模型的建立过程,并与常用的对流层区域实时模型进行了对比.还讨论了建模测站数目对预报精度的影响.相比现有的其他对流层延迟模型,基于改进的BP神经网络构建的区域精密对流层延迟模型无论在拟合和预报方面都有较好的精度,且随着测站数目的增加模型精度趋于平稳.改进的模型参数较少,可以进行实时的区域精密对流层延迟改正;需要播发的信息量小,适用于连续运行参考站系统（Continuously Operating Reference Stations,CORS）的应用.研究表明：改进的BP神经网络模型能够更好的充分利用大规模历史数据描述卫星信号对流层延迟的空间分布情况,适用于实时大区域精密对流层建模.基于日本地区2005年近1000多个测站的NCAR（National Center Atmospheric Research）对流层数据进行区域对流层延迟建模,结果表明改进的BP神经网络模型在拟合和预报精度上都有较大提升,RMSE（Root Mean Square Error）分别为：7.83 mm和8.52 mm,而四参数模型拟合、预报RMSE分别18.03 mm和16.60 mm.     

镇江地震台网理论监测能力评估

基于近震震级公式,对镇江地震台网理论监测能力进行评估,绘制地震监测能力图,以确定监测区不同地点发生地震时能被台网有效分析和定位的地震最小震级。镇江市句容县在该台网理论监测震级最小,为ML1.2—1.3;在镇江及相邻城市,发生M_L 1.8分析认为,以上地震均能被有效监测。     

Extracting drainage networks and their connectivity using LiDAR data

Policies, measures, and models geared towards flood prevention and managing surface waters benefit from high quality data on the presence and characteristics of drainage ditches. As a cost and labour effective alternative for acquiring such data through field surveys, we propose a method (a) to extract vector data representing ditch drainage networks based on local morphologic features derived from high resolution digital elevation models (DEM) and (b) to identify possible connections in the ditch network by calculating a probability of the connectivity using a logistic regression where the predictor variables are characteristics of the ditch centre lines or derived from the DEM. Using Light Detection and Ranging (LiDAR) derived DEMs with a 1 m resolution, the method was developed and tested for a mixed agricultural residential area in north‐eastern Belgium. The derived ditch segments had an error of omission of 8% and an error of commission of 5%. The original positional accuracy of the centre lines of the extracted ditches was 0.6 m and could be improved to 0.4 m by shifting each vertex to the position of the lowest LiDAR point located within a radius equal to the spatial resolution of the used DEM. About 69% of the false disconnections in the network were identified and corrected leading to a reduction of the unconnected parts of the ditch network by 71%. The extracted and connected network approximated the reference ditch network fairly well.     

测震台网数据传输补数技术

针对测震台网波形数据传输中断导致丢数现象,开发测震台网自动补数系统SDARS,自动检测数据丢失现象,并从地震台数据采集器下载缺失数据;设计手动辅助补数工具软件SeisDataUtil,提供不同格式的地震数据文件的手动补数功能。通过此套补数系统,有效提高测震台网波形数据完整率,最小化减少波形数据丢失。     

钻孔应变观测技术发展方向探讨

从大地测量技术、地震观测技术和钻孔应变观测技术３种地面运动观测方法在观测频频带和观测精度方面的互补性,探讨了钻孔应变观测技术的发展方向,指出钻孔应变观测应将观测重点放在周期数十秒到数十天的短临信息频段,同时指出,钻孔应变观测可以同时用于声和高频地震观测,以获取更多的短临信息。     

红水河梯级水电站水库地震监测台网的建设与发展

水库地震监测是我国地震监测的重要组成部分。文中阐述了红水河梯级水电站水库地震监测台网的建设发展历程,详细介绍了天生桥一级、龙滩、岩滩、大化及大藤峡水库专用地震监测台网的建设和发展,并对比分析了库区蓄水前后的地震活动记录,讨论了水库地震监测台网面临的升级改造及运行管理等问题,建议采用流域化统一管理。     

Are artificial neural network techniques relevant for the estimation of longitudinal dispersion coefficient in rivers? / Les techniques de réseaux de neurones artificiels sont-elles pertinentes pour estimer le coefficient de dispersion longitudinale en rivières?

Abstract

Abstract Accurate application of the longitudinal dispersion model requires that specially designed experimental studies are performed in the river reach under consideration. Such studies are usually very expensive, so in order to quantify the longitudinal dispersion coefficient, as an alternative approach, various researchers have proposed numerous empirical formulae based on hydraulic and morphometric characteristics. The results are presented of the application of artificial neural networks as a parameter estimation technique. Five different cases were considered with the network trained for different arrangements of input nodes, such as channel depth, channel width, cross-sectionally averaged water velocity, shear velocity and sinuosity index. In the case where the sinuosity index is included as an input node, the results turned out to be better than those presented by other authors.