An ultra-shallow water storm surge model with quadratically depth-varying eddy viscosity and its application to the numerical modelling of the Bohai Sea storm surges

Based on the ultra-shallow water storm surge theory proposed by Qin and Feng^[1] (1975), an ultra-shallow water storm surge model, taking into consideration the effect of the earth's rotation and the quadratically depth-varying eddy viscosity, is developed. Using the model wind stress fields as a guide for representing the effect of wind stress forcing in our model, a numerical investigation of the Bohai Sea wind surge is made. As a better means for solving the mathematical model, the Galerkin finite element technique is employed in numerical solutions. Under the control of the main weather situation, namely, the cold wave combined with the extratropical cyclone, two storm surge processes experienced on the Bohai Sea are simulated numerically. It is found that the experimental results, in the main, are in agreement with the observations.     

城市暴雨的细化预测实例分析

为了提高暴雨预测准确率和降低城市暴雨造成的危害和损失。使用大气探空和自动气象站1次份钟的观测资料,以“信息确定性”和“时间不占有物质维”的观点,采用非规则信息数字化分析方法,对城市暴雨预测进行实用性分析。结合2004年6月29日至30日成都地区的暴雨实例,通过将复杂的数量信息转化为方位角的相空间结构信息,对暴雨发生前后的风速、风向、温度、湿度分别进行相空间分析,结果表明相空间图配合V-30结构图能够对城市暴雨进行细化预测。     

一种考虑PMX与PMY之间相关性的极移预报新方法

提出采用多元回归模型（MAR）与最小二乘（LS）组合进行极移预报。该模型考虑极移PMX和PMY的LS拟合残差之间的相关性,采用PMX残差和PMY残差一起构建预报模型进行残差预报。通过与LS+AR预报结果的对比表明,LS+MAR模型的预报结果更优。此外,通过与EOP_PCC预报结果的对比也说明,LS+MAR模型的短期极移预报精度能够达到国际先进水平。     

The Characteristics of Storm Wave Behavior and Its Effect on Cage Culture Using the ADCIRC+SWAN Model in Houshui Bay,China

The current storm wave hazard assessment tends to rely on a statistical method using wave models and fewer historical data which do not consider the effects of tidal and storm surge.In this paper,the wave-current coupled model ADCIRC+SWAN was used to hindcast storm events in the last 30 years.We simulated storm wave on the basis of a large set of historical storms in the North-West Pacific Basin between 1985 and 2015 in Houshui Bay using the wave-current coupled model ADCIRC+SWAN to obtain the storm wave level maps.The results were used for the statistical analysis of the maximum significant wave heights in Houshui Bay and the behavior of wave associated with storm track.Comparisons made between observations and simulated results during typhoon Rammasun(2014)indicate agreement.In addition,results demonstrate that significant wave height in Houshui Bay is dominated by the storm wind velocity and the storm track.Two groups of synthetic storm tracks were designed to further investigate the worst case of typhoon scenarios.The storm wave analysis method developed for the Houshui Bay is significant in assisting government's decision-making in rational planning of deep sea net-cage culture.The method can be applied to other bays in the Hainan Island as well.     

基于GIS的单元簇遗传建模及其在区域矿产预测中的应用

论述一种GIS支持下的基于"单元簇”概念和遗传建模的多源地学信息综合分析方法及在多目标矿产预测中的应用.在以往矿产定量预测中,根据随机抽样思想进行单元划分,对空间信息利用不够充分.用单元的空间组合("单元簇”)代替单元作为定量类比的基本单位,从而能较好实现地质变量值及其所反映的局部地质空间结构的定量类比;将单元作为GIS区图元,利用GIS空间分析功能实现对单元及单元簇的管理和操作;以已知样品判对率最大为适应值计算准则,用遗传算法建立线性判别函数,可快速有效地实现多目标矿产定位预测.以新疆康古尔塔格地区金矿预测实例说明了其应用效果.     

A preliminary study on the intensity of cold wave storm surges of Laizhou Bay

Dike failure and marine losses are quite prominent in Laizhou Bay during the period of cold wave storm surges because of its open coastline to the north and flat topography. In order to evaluate the intensity of cold wave storm surge, the hindcast of marine elements induced by cold waves in Laizhou Bay from 1985 to 2004 is conducted using a cold wave storm surge–wave coupled model and the joint return period of extreme water level, concomitant wave height, and concomitant wind speed are calculated. A new criterion of cold wave storm surge intensity based on such studies is developed. Considering the frequency of cold wave, this paper introduces a Poisson trivariate compound reconstruction model to calculate the joint return period, which is closer to the reality. By using the newly defined cold wave storm surge intensity, the ‘cold wave grade' in meteorology can better describe the severity of cold wave storm surges and the warning level is well corresponding to different intensities of cold wave storm surges. Therefore, it provides a proper guidance to marine hydrological analysis, disaster prevention and marine structure design in Laizhou Bay.     

Landslide prediction based on improved principal component analysis and mixed kernel function least squares support vector regression model

Landslide probability prediction plays an important role in understanding landslide information in advance and taking preventive measures. Many factors can influence the occurrence of landslides, which is easy to have a curse of dimensionality and thus lead to reduce prediction accuracy. Then the generalization ability of the model will also decline sharply when there are only small samples. To reduce the dimension of calculation and balance the model's generalization and learning ability, this study proposed a landslide prediction method based on improved principal component analysis(PCA) and mixed kernel function least squares support vector regression(LSSVR) model. First, the traditional PCA was introduced with the idea of linear discrimination, and the dimensions of initial influencing factors were reduced from 8 to 3. The improved PCA can not only weight variables but also extract the original feature. Furthermore, combined with global and local kernel function, the mixed kernel function LSSVR model was framed to improve the generalization ability. Whale optimization algorithm(WOA) was used to optimize the parameters. Moreover, Root Mean Square Error(RMSE), the sum of squared errors(SSE), Mean Absolute Error(MAE), Mean Absolute Precentage Error(MAPE), and reliability were employed to verify the performance of the model. Compared with radial basis function(RBF) LSSVR model, Elman neural network model, and fuzzy decision model, the proposed method has a smaller deviation. Finally, the landslide warning level obtained from the landslide probability can also provide references for relevant decision-making departments in emergency response.     

Synthetic information prediction system for crisis mine based on GIS

Reserves of some kinds of the crisis mines will be lack now or from now on, because of lacking seriously reserves of mineral resources and the crisis of exploring bases in support. So that it is urgent to predict, appraise, development and utilize the replaceable resources of the crisis mines. The mineral resources prediction software system of synthetic information is intelligent GIS which is used to quantitative prediction of large-scale synthetic information mineral target. It takes the geological body and the mineral resource body as a unit. And it analyzes the ore deposit genesis and metallotect, knows the spatial distribution laws of the ore deposit and ore body, and establish the prospecting modelbased on the concept of establishing the three-dimensional space of a mine. This paper will primarily discuss some important problems as follows： the secondary development of various kinds of data（ including geology, geophysical prospecting, geochemical prospecting and remote sensing, etc）; process synthetically and establish the synthetic information interpretative map base; correspond prospecting model with synthetic information of ore deposit; divided into statistical units of metallogenic information synthetic anomalies based on the synthetic information anomalies of ore control, then research the metallogenic information variable of unit synthetically and make quantitative prediction according to choose the quantitative prediction math model which is suitable to the demands of large-scale precision; at last, finish the target area optimization of ore deposit （body）.     

南郑福成奥陶系与志留系分界线附近的沉积岩特征

本文通过对陕西南郑福成奥陶系—志留系界线上下沉积相、沉积旋回、事件地层、海水淡化程度以及地球化学等方面特征的研究,佐证了将本剖面奥陶系—志留系界线置于Glyptograptus persculptus带之底或Diplograptus bohemicus带之顶的合理性。     

Synthetic information prediction system for crisis mine based on GIS

Reserves of some kinds of the crisis mines will be lack now or from now on, because of lacking seriously reserves of mineral resources and the crisis of exploring bases in support. So that it is urgent to predict, appraise, development and utilize the replaceable resources of the crisis mines. The mineral resources prediction software system of synthetic information is intelligent GIS which is used to quantitative prediction of large-scale synthetic information mineral target. It takes the geological body and the mineral resource body as a unit. And it analyzes the ore deposit genesis and metallotect, knows the spatial distribution laws of the ore deposit and ore body, and establish the prospecting model based on the concept of establishing the three-dimensional space of a mine. This paper will primarily discuss some important problems as follows: the secondary development of various kinds of data(including geology, geophysical prospecting, geochemical prospecting and remote sensing, etc); process synthetically and establish the synthetic information interpretative map base; correspond prospecting model with synthetic information of ore deposit; divided into statistical units of metallogenic information synthetic anomalies based on the synthetic information anomalies of ore control, then research the metallogenic information variable of unit synthetically and make quantitative prediction according to choose the quantitative prediction math model which is suitable to the demands of large-scale precision; at last, finish the target area optimization of ore deposit (body).     

基于EEMD的大坝变形多步预测方法研究

针对大坝变形具有非线性和非平稳性的特点,提出一种基于集合经验模态分解(EEMD)的大坝变形多步预测新算法。首先从时频分析出发,利用集合经验模态分解将变形时间序列分解成具有不同频率特征的分量;然后采用游程判定法对波动程度相似的分量重构为高、中和低频3个分量;最后对3个分量分别建立相应的多步预测模型,叠加各预测值即为最终预测结果。经算例验证,并与AR模型、BP神经网络和支持向量机的多步预测进行对比分析,同时建立不同预测步长进一步验证。结果表明,该算法预测精度较高,在大坝变形波动剧烈的时段也能保证较好的预测效果,可以应用于大坝变形预测。     

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分数阶傅里叶变换联合支持向量机的建筑物变形预测

提出一种分数阶傅里叶变换(fractional Fourier transformation, FrFT)与支持向量机(support vector machine, SVM)相结合的建筑物变形组合预测模型。首先利用FrFT对变形时间序列进行多尺度分析,将复杂时间序列分解为一系列结构较为简单的子序列;然后利用SVM对每个子序列分别建立预测模型,通过将各个子序列的预测结果进行综合叠加,得到最终预测结果;同时考虑到SVM模型参数选择的难题,提出一种改进果蝇优化算法(improved fruit fly optimization algorithm, IFOA)对其进行全局寻优,提升预测性能。以西南地区某混凝土坝变形实测数据为例开展验证实验,结果表明,本文组合预测模型能够充分挖掘数据中隐含的趋势性和规律性信息,获得较高的预测精度。     

一种基于改进SEIR模型的突发公共卫生事件风险动态评估与预测方法——以欧洲十国COVID-19为例

突发公共卫生事件会严重影响社会公众生命健康,风险评估和预测可为突发公共卫生事件有效防控提供科学依据.本文提出了一种基于SEIR模型的突发公共卫生事件风险动态评估与预测方法,将突发公共卫生事件传播与人口、医疗、经济情况相结合,耦合危险性与脆弱性,建立合理的风险评估综合指标体系,利用熵值一层次分析组合模型实现突发公共卫生事...     

孟加拉湾风暴暴雨的能量分析

利用MMSV3中尺度数值预报模式对2004年5月18-19日造成云南暴雨过程的孟湾风暴进行了数值模拟，在模拟结果与实况较为一致的基础上，利用辐散风和旋转风动能平衡方程，分析盂湾风暴的能量收支和转换特征，揭示孟加拉湾风暴维持的机制及其与外围暴雨增幅的关系。     

多模态地理大数据时空分析方法

多模态地理大数据时空分析旨在融合地理大数据的多模态信息发现有价值的时空分布规律、异常表现、关联模式与变化趋势,是全空间信息系统的核心研究内容,并有望成为推进地理学人地关系研究的重要突破口。为应对地理大数据时代的新机遇与挑战,本文围绕4类核心的时空分析方法（时空聚类分析、时空异常分析、时空关联分析与时空预测分析）,系统归纳了国内外研究现状,探讨了时空分析中多尺度建模、多视角协同、多特征认知与多特性表达的研究难点。进而,介绍了多模态地理大数据时空聚类、异常、关联与预测分析模型,更加全面、客观、精准地认知与理解时空大数据中潜在的地理知识,并且能够在气象环境监测、公共安全管理、城市设施规划等多个应用领域发挥关键作用。     

顾及上网行为特征的手机用户停留行为预测方法

随着信息通讯技术的发展,手机成为人类日常生活不可缺少的一部分,人类活动逐渐从现实空间延伸至网络空间,在移动互联网时代,网络空间的上网行为与现实空间的出行行为密不可分。当前个体出行行为预测建模较少考虑上网行为与出行行为间的关系,本文提出一种融合上网行为特征的手机用户停留行为预测模型,通过时空约束定义手机用户的停留行为,在考虑个体出行行为时空偏好的同时,融合手机用户使用的APP组合、上网流量、上网次数等上网行为特征以及天气信息等外部特征,从时间、空间的角度进行特征交叉,构建从特征到模型均具有高可解释性的手机用户停留行为预测模型。实验证明：本文模型预测准确率为80.31%,且在融合上网行为特征、天气等外部因素后,比仅使用个体出行特征进行手机用户停留行为预测提升了12.08%。     

An Elliptical Wind Field Model of Typhoons

1　Introduction　Thestormsurgeisoneofthemostimportantphe nomenathatendangerthecoastalengineeringfacili ties .Everyyearthereareabout 1 2tropicalcyclonesmakinglandfallatthemainlandofChinafromMaytoOctober (MuandTu ,2 0 0 0 ) .Whentheastronomictideishigh ,the…     

Nonlinear interaction between astronomical tides and storm surges at wusong tidal station

There are obvious periodic oscillations in the observations of storm surges in the East China Sea. The storm surges are not only controlled by the wind stresses and isolated long wave caused by typhoons but also affected by the interaction between astronomical tides and storm surges. In the present paper we simulate the interaction between tides and storm surges by using a two dimensional numerical model. In our numerical experiments we use the data of the storm surge induced by Typhoon 8114. The calculations tally with the measured data well. The results indicate that the periodic oscillations occurring in the elevations of the surge are mainly caused by the interaction between the tide and the storm surge. The numerical experiments also indicate that the forecasting precision may be notably improved if the nonlinear interaction between tides and storm surges is taken into account.     

A high resolution forecast model of storm surge inundation

In order to forecast storm surge inundation, a two-dimensional model is established. In the model, an alternating computation sequence method is used to solve the governing equations, and the dry and wet method is introduced to treat the moving boundary. This model is easy to use. It has a friendly input interface and Arcview GIS is used as the output interface. The model is applied to the Shantou area to simulate the storm surge elevations and inundations caused by Typhoons 6903 ane 0104 using the same relevant parameters. The calculated results agree well with the observations.