模糊优选神经网络模型在城市防洪规划方案优选中的应用

城市防洪规划方案的综合优选是一个涉及到政治、社会、经济、环境等多准则、多因素的复杂多目标决策问题.针对目前各种常用的综合优选模型应用中存在的指标权重选择及转换问题,利用模糊优选神经网络模型,构造了合理的网络拓扑结构并将模型应用于某城市的防洪规划方案综合优选中.实例结果表明,此模型不仅避免了对指标权重的处理问题,而且明显加快了BP网络的收敛速度.     

Algorithm Studies on How to Obtain a Conditional Nonlinear Optimal Perturbation (CNOP)

The conditional nonlinear optimal perturbation (CNOP), which is a nonlinear generalization of the linear singular vector (LSV), is applied in important problems of atmospheric and oceanic sciences, including ENSO predictability, targeted observations, and ensemble forecast. In this study, we investigate the computational cost of obtaining the CNOP by several methods. Differences and similarities, in terms of the computational error and cost in obtaining the CNOP, are compared among the sequential quadratic programming (SQP) algorithm, the limited memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) algorithm, and the spectral projected gradients (SPG2) algorithm. A theoretical grassland ecosystem model and the classical Lorenz model are used as examples. Numerical results demonstrate that the computational error is acceptable with all three algorithms. The computational cost to obtain the CNOP is reduced by using the SQP algorithm. The experimental results also reveal that the L-BFGS algorithm is the most effective algorithm among the three optimization algorithms for obtaining the CNOP. The numerical results suggest a new approach and algorithm for obtaining the CNOP for a large-scale optimization problem.     

一种基于定向技术的Ad Hoc路由协议

基于MAC层的定向技术&提出了一种适合于Ad hoc无线网络的协议APRP协议,协议考虑了MAC层和网络层信息的共享和交互,改进了动态源路由协议DSR的路由发现和路由维护机制.采用NS2工具对协议性能进行了仿真研究,结果表明APRP协议不仅可以利用定向技术能量利用率的优势,而且还能较好地保持节点移动情况下的吞吐量,降低端到端数据包延时和路由开销     

EXPERIMENTS TO TRACK STORMS USING MODERN OPTIMIZATION ALGORITHMS

Storm identification and tracking based on weather radar data are essential to nowcasting and severe weather warning. A new two-dimensional storm identification method simultaneously seeking in two directions is proposed, and identification results are used to discuss storm tracking algorithms. Three modern optimization algorithms (simulated annealing algorithm, genetic algorithm and ant colony algorithm) are tested to match storms in successive time intervals. Preliminary results indicate that the simulated annealing algorithm and ant colony algorithm are effective and have intuitionally adjustable parameters, whereas the genetic algorithm is unsatisfactorily constrained by the mode of genetic operations. Experiments provide not only the feasibility and characteristics of storm tracking with modern optimization algorithms, but also references for studies and applications in relevant fields.     

GIS中河网空间数据模型

河网通常是由多条河流组成的,河网的空间形态结构特征由各条河流的几何特征和河流之间的相互关系决定,为了完整表示河网的空间形态结构特征,本文提出了基于河网空间形态结构特征的河网空间数据模型,并阐述了该模型的建立、维护等方法。     

Effects of strong ground motion on the susceptibility of gully type debris flows

Typhoon Herb in 1996 caused widespread debris flows in central Taiwan. The 7.3 Chi-Chi earthquake on September 21, 1999, which also took place in central Taiwan, induced many landslides in the region. These landslides turned into debris flows when Typhoon Toraji struck Taiwan in 2001. This research selects three regions which suffered a ground motion class of 5, 6, and 7 on the Richter scale during the Chi-Chi earthquake as study areas. Air photos from 1997 and 2001 of these regions are used to map the gully-type debris flows that took place after Typhoons Herb and Toraji, respectively. The gullies adjacent to the debris flow, but without a trace of debris flows, are also mapped as the non-debris flow data. The topography, hydrogeology, and rainfall factors – where debris flow occurred and in which there was no occurrence of debris flows in these gullies were retrieved from DTM, geological maps, and iso-countour maps, and of rainfall through GIS processing. These characteristic are introduced into a probabilistic neural network to build a predicting model for the probability of the occurrence of debris flows. Three series of cross analyses are conducted to compare the probability of the occurrence of debris flows of the same dataset predicted by different prediction models. The results reveal that the susceptibility of debris flows was elevated after the Chi-Chi earthquake struck. The upsurge of susceptibility was more obvious for the regions that received a higher class of ground motion.     

网络分析方法在GPS控制网优化设计中的应用

讨论了网络分析方法中的深度优先遍历算法在GPS控制网优化设计中资源配置问题中的应用,并在该算法的基础上,进行了一定的改进,提出了并行项目的解决建议,为网络的资源配置提出了一种新的解决方法。     

Swarm intelligence-based solver for parameter estimation of laboratory through-diffusion transport of contaminants

Theoretical approaches are of fundamental importance to predict the potential impact of waste disposal facilities on ground water contamination. Appropriate design parameters are generally estimated by fitting theoretical models to data gathered from field monitoring or laboratory experiments. Transient through-diffusion tests are generally conducted in the laboratory to estimate the mass transport parameters of the proposed barrier material. These parameters are usually estimated either by approximate eye-fitting calibration or by combining the solution of the direct problem with any available gradient-based techniques. In this work, an automated, gradient-free solver is developed to estimate the mass transport parameters of a transient through-diffusion model. The proposed inverse model uses a particle swarm optimization (PSO) algorithm that is based on the social behavior of animals searching for food sources. The finite difference numerical solution of the forward model is integrated with the PSO algorithm to solve the inverse problem of parameter estimation. The working principle of the new solver is demonstrated and mass transport parameters are estimated from laboratory through-diffusion experimental data. An inverse model based on the standard gradient-based technique is formulated to compare with the proposed solver. A detailed comparative study is carried out between conventional methods and the proposed solver. The present automated technique is found to be very efficient and robust. The mass transport parameters are obtained with great precision.     

General seismic wave and phase detection software driven by deep learning

We developed an automatic seismic wave and phase detection software based on PhaseNet, an efficient and highly generalized deep learning neural network for P- and S-wave phase picking. The software organically combines multiple modules including application terminal interface, docker container, data visualization, SSH protocol data transmission and other auxiliary modules. Characterized by a series of technologically powerful functions, the software is highly convenient for all users. To obtain the P- and S-wave picks, one only needs to prepare three-component seismic data as input and customize some parameters in the interface. In particular, the software can automatically identify complex waveforms (i.e. continuous or truncated waves) and support multiple types of input data such as SAC, MSEED, NumPy array, etc. A test on the dataset of the Wenchuan aftershocks shows the generalization ability and detection accuracy of the software. The software is expected to increase the efficiency and subjectivity in the manual processing of large amounts of seismic data, thereby providing convenience to regional network monitoring staffs and researchers in the study of Earth's interior.     

青藏高原河流网络高分CubeSat遥感监测

河流网络是地表水循环的重要组成部分,如何实现河流网络动态监测已成为河流遥感研究的热点。近年来,以PlanetScope为代表的CubeSat小卫星已具备了米级空间分辨率、1 d重访周期的优势,这为河流网络高时空分辨率动态监测提供了可能。本文以青藏高原长江源区的通天河流域（227 km²）为研究区,选取2017-05—2017-10 5期3 m空间分辨率CubeSat遥感影像,增强河流横纵剖面特征自动化提取了河流网络,研究了通天河流域河流网络动态变化,对比分析了3 m CubeSat与30 m Landsat 8、10 m Sentinel-2所提取的河流网络,以及5种现有水体数据集（GRWL,GSW,FROM-GLC 2017,OpenStreetMap,HydroSHEDS）。研究结果表明：（1）研究区内河流网络5月水系密度较低（0.38 km^-1）,7—8月河流网络进入丰水期,水系密度显著增加至0.61 km^-1,9月河流网络进入平水期,水系密度趋于平稳（0.53 km^-1）,随后迅速退化并于10月开始冻结,水系密度迅速降低至0.37 km^-1;（2）采用高空间分辨率CubeSat所提取的河流网络能够识别更多细小河流（河宽3—30 m）,CubeSat所提取的河流总长分别为Landsat 8、Sentinel-2所提取河流总长的1.6倍和1.3倍;（3）CubeSat所提取的河流网络水系密度高于现有水体数据集（2.9—12.4倍）,弥补了现有水体数据集无法反映细小河流的不足。