Improving Numerical Weather Prediction in Low Latitudes by Optimizing Diffusion Coefficients

The horizontal diffusion coefficients of the operational model (T42L9) in numerical weather prediction are optimized by the steepest descent search of multi-dimensional optimization. In order to improve prediction accuracy in low latitudes, the optimum horizontal diffusion coefficients are chosen, with changing variation of the basic diffusion coefficient with the passage of time, and later forecasts are also made better. In view of the averages of forecast verifications of 9 cases, the forecasts with optimum diffusion coefficients are an improvement on operational forecasts. It means that the forecasts are got much better with optimum values of some important parameters by optimization in numerical weather prediction.     

Ethnicity,Housing Search,and the Role of the Real Estate Agent: A Study of Portuguese and Non-Portuguese Real Estate Agents in Toronto*

This study concerns the behavior and practices of real estate agents in the housing search process. The research investigates whether the information provided and houses recommended by agents working for Portuguese firms differ from the recommendations of agents working for firms owned by non-Portuguese brokers in the cities of Toronto and Mississauga (a western suburb of Toronto), Canada. Data for the study were obtained from a participant observation study of a sample of real estate agents. Empirical evidence indicates that the ethnicity of real estate agents (Portuguese versus non-Portuguese) and the brokers for whom they work (Portuguese-owned firms versus non-Portuguese-owned firms) determine to a considerable extent the marketing strategies of agents and the neighborhoods they recommend.     

水文地质参数识别的快速和谐搜索算法

将一种新的启发式和谐搜索算法(harmony search algorithm,HS)引入到水文地质领域。在对其音节调整步骤进行改进的基础上,提出快速和谐搜索算法(Fast harmony search algorithm,FHS),并将FHS算法与MODFLOW结合,用于水文地质问题的参数识别。算例研究表明,FHS算法较其他多种算法具有更强的全局搜索能力、更快的收敛速度及求解精度,可用于地下水数值模型的参数反演。     

基于禁忌搜索的目标图像信息隐藏技术

信息隐藏技术是解决重要目标图像信息网上传输安全的一种有效手段,隐藏的信息量和不可感知性是一个矛盾的两个方面。在对重要目标信息进行隐藏时,必须在二者之间做一个权衡。如何在满足不可感知性的前提下隐藏尽町能多的信息是追求的目标。提出了基于禁忌搜索的图像信息的隐藏技术,可以很好地解决这个问题。     

Homogeneous Velocity Models of The West Bohemian Swarm Region Obtained By Grid Search

West Bohemian earthquake swarms are used to determine the parameters of simple homogeneous velocity models of the individual subregions of the given area, based on a group of earthquakes that occurred in these subregions. The grid search method is used for location. Models yielding the minimum sum of squares of the travel-time residua in locating the whole group of earthquakes in the given subregion are considered suitable. Relocation obtained by grid search is compared with that obtained by the FASTHYPO method. The computations indicate that the subregions under consideration can be, from the point of view of earthquake location, sufficiently represented by homogeneous models, but the models differ for the data from different subregions. The velocities of these models are given. The models under consideration are compared with some of the previously published 1-D models of the broader region of Western Bohemia.     

震后倒塌建筑物的处理:遇难人员搜寻与废墟清理

汶川地震及近几年国内外发生的一些破坏性地震灾害中,在应急期的幸存者搜救行动之后,倒塌建筑物的处理问题已经逐渐凸显出来,其中重点是对遇难人员的搜寻和对废墟的清理。本文通过对2010年海地地震和2011年新西兰地震救援的实际经验的总结,分析了如何科学、有序地开展废墟的清理和遇难人员的搜寻工作,包括对新西兰地震震害情况的概述、主要建筑物破坏情况的描述和搜救的基本过程。对重型机械的使用、人工破拆处理和遗体鉴别这3个关键环节进行了重点阐述,并对存在的问题进行了讨论。     

基于多重随机k维树地震搜索引擎的建立

描述了数据库的构建、利用多重随机k维树建立地震搜索引擎的过程。通过实际搜索测试,证明了利用地震搜索引擎确定震源信息的可行性,并探讨了其存在的问题及相应的改进措施。结果表明,地震搜索引擎能够自动、快速的确定震源信息,具有很强的实用性。     

A Real-time Lithological Identification Method based on SMOTE-Tomek and ICSA Optimization

In petroleum engineering, real-time lithology identification is very important for reservoir evaluation, drilling decisions and petroleum geological exploration. A lithology identification method while drilling based on machine learning and mud logging data is studied in this paper. This method can effectively utilize downhole parameters collected in real-time during drilling, to identify lithology in real-time and provide a reference for optimization of drilling parameters. Given the imbalance of lithology samples, the synthetic minority over-sampling technique (SMOTE) and Tomek link were used to balance the sample number of five lithologies. Meanwhile, this paper introduces Tent map, random opposition-based learning and dynamic perceived probability to the original crow search algorithm (CSA), and establishes an improved crow search algorithm (ICSA). In this paper, ICSA is used to optimize the hyperparameter combination of random forest (RF), extremely random trees (ET), extreme gradient boosting (XGB), and light gradient boosting machine (LGBM) models. In addition, this study combines the recognition advantages of the four models. The accuracy of lithology identification by the weighted average probability model reaches 0.877. The study of this paper realizes high-precision real-time lithology identification method, which can provide lithology reference for the drilling process.     

车载激光扫描数据中杆状地物提取

针对车载激光扫描数据中对杆状地物提取效果不够理想的问题,该文提出一种基于聚类的杆状地物提取方法。首先将原始点云投影到水平面并进行格网划分,以单个格网为数据处理单元去除地面点;再基于处理数据对格网进行点云探测并编号,赋予同一属性值利用八邻域搜索对地物点聚类;然后以聚类后单个点云块为处理单元,利用各类地物特征,如高度、投影点密度、投影面积及形状等,逐步排除其他地物点,实现对杆状地物的精细提取。试验验证了文中所述方法对道路环境中杆状地物提取的有效性。     

输出误差系统的多新息辨识方法

研究了输出误差(OE)系统和输出误差自回归滑动平均(OEARMA)系统(即Box-Jenkins系统)的辅助模型随机梯度算法、辅助模型多新息随机梯度算法、辅助模型递推最小二乘算法、辅助模型多新息最小二乘算法,输出误差系统的修正辅助模型随机梯度算法、遗忘因子辅助模型随机梯度算法、变递推间隔辅助模型随机梯度算法、变递推间隔辅助模型多新息随机梯度算法、变递推间隔辅助模型递推最小二乘算法等,以及输出误差自回归(OEAR)系统的基于滤波的辅助模型多新息广义随机梯度算法和基于滤波的辅助模型多新息广义最小二乘算法.