概率天气预报的兴起及其社会经济意义

作者试图从辨证法观点分析概率天气预报之所以兴起的认识论动机和社会经济动机，指出了概率天气预报的产生既是人对天气气候变化同时具有确定性和随机性的认识不断深化的结果，也是社会经济发展到一定阶段，经济决策日益定量经和精细化客观需要，阐述了气象－经济决策这一跨学科领域与概率天气预报之间的相互关系，并有一个简单的气象经济决策模式从理论上和实例计算结果证明了概率天气预报比传统的天气预报更高的经济价值。     

The design storm concept in flood control design and planning

The design storm approach, where the subject criterion variable is evaluated by using a synthetic storm pattern composed of identical return frequencies of storm pattern input, is shown to be an effective approximation to a considerably more complex probabilistic model. The single area unit hydrograph technique is shown to be an accurate mathematical model of a highly discretized catchment with linear routing for channel flow approximation, and effective rainfalls in subareas which are linear with respect to effective rainfall output for a selected “loss” function. The use of a simple “loss” function which directly equates to the distribution of rainfall depth-duration statistics (such as a constant fraction of rainfall, or a ?-index model) is shown to allow the pooling of data and thereby provide a higher level of statistical significance (in estimating T-year outputs for a hydrologic criterion variable) than use of an arbitrary “loss” function. The above design storm unit hydrograph approach is shown to provide the T-year estimate of a criterion variable when using rainfall data to estimate runoff.     

岩体结构随机模型模拟方法

本文论述利用勘探平硐资料研究岩体结构面分布规律及进行岩体结构面随机模型模拟方法。文中首先论述了描述结构面空间分布规律的五个几何参数,即产状、形态、规模、密度和张开度及其相应的概率分布型式;其次简单的介绍了 Monte-Carlo 方法在模拟结构面分布中的应用;最后结合三峡工程实例,论述了利用坝基勘探平硐编录图及现场记录估计结构面产状、迹线长度、中点密度分布参数的方法,并且给出了在参数估计基础上进行 Monte-Carlo模拟的部分结果。本文为岩体结构力学分析提供了一个定量的结构模型。     

Probabilistic approach to short- and intermediate-term earthquake forecasting: II test application to southern California

A method is proposed for assessing the modifying effects of precursory observations on long-term probabilities of strong earthquakes (M6). Estimated short-and intermediate-term probabilities so estimated rely on the mean precursory time and its uncertainty as a function of the mainshock magnitude and epicentral position. Short-and intermediate-term modification of long-term probabilities within a 120,000 km² circular area covering most of Southern California are estimated for one or more observations of strain, resistivity, and ground water anomalies centered near Palmdale in the central Transverse Ranges. The principal assumptions employed are log normal distribution of globally reported waiting periods and assumed predictive reliability of precursory phenomena. As expected, the significance of short-and intermediate-term modifications scale with the reliability of precursory observations, and are particularly enhanced within window lengths of a precursory characteristic time.     

A generalized probabilistic approach for slope analysis

Summary A new probabilistic approach is introduced for slope stability analysis, which is general in types of variable distributions and correlations or dependency between variables, and flexible enough to include any adverse impact analysis for blasting vibrations and groundwater conditions.The material strength within a slope area, given in terms of the internal friction angle (ø) and cohesion (c), is randomized in the bivariate joint probability analysis. To be a completely general engineering method, the new probabilistic approach employs the random variable transformation technique: the Hermite model of the Gaussian transformation function, which transforms the experimental histogram of shear strength parameters to the standard Gaussian distribution (=0, ²=1.0).Because a binormal joint probability is analysed on the true probability region projected on the plane of the Gaussian transformed variables, it is an exact solution of slope stability based on the available sample data. No assumption on the shape of the experimental histogram or independency between two random variables is made as in the current probability methods of slope analysis.     

Probabilistic neural networks for seismic damage mechanisms prediction

The procedure commonly employed to assess the seismic vulnerability of buildings uses simplified qualitative and quantitative observations obtained from the measured data entered into report forms. In Italy, the data sheets adopted by the National Defence Group against Earthquakes (Gruppo Nazionale per la Difesa dai Terremoti—GNDT) play a unifying and reference role. This paper proposes a method for the processing of the data contained in such report forms which is based on probabilistic neural networks producing a Bayesian classification. The final goal is to exploit the fundamental learning and generalization capabilities of neural networks to obtain an estimate of the vulnerability of structural systems. In particular, the aim is to be able to predict the damage mechanisms which may be triggered in the macro-elements of public worship buildings. Copyright © 1999 John Wiley & Sons Ltd.     

中国东南地区复杂地形下降水概率预报的订正研究

使用TIGGE (the THORPEX interactive grand global ensemble)资料集下欧洲中期天气预报中心(the European Centre for Medium-Range Weather Forecasts, ECMWF)逐日起报的预报时效为24～168 h的日降水量集合预报资料,集合预报共包括51个成员,利用左删失的非齐次Logistic回归方法(left-Censored Non-homogeneous Logistic Regression, CNLR)和标准化的模式后处理方法(Standardized Anomaly Model Output Statistics, SAMOS)对具有复杂地形的中国东南部地区降水预报进行统计后处理。结果表明：采用CNLR方法能够有效改进原始集合预报的平均绝对误差(Mean Absolute Error, MAE)和连续分级概率评分(Continuous Ranked Probability Score, CRPS),提升了降水的定量预报和概率预报的预报技巧。而使用SAMOS方法对数据进行预处理,考虑地形...     

基于Bayes网络的多粒度时空对象地理过程演化建模——以新安江模型为例

多粒度时空对象具有多粒度、多类型、多形态、多参照系、多元关联、多维动态、多能自主特点,可用于直接描述从微观到宏观的现实世界.基于时空对象建模理论构建多尺度地理对象耦合演化的集成表达是多粒度时空对象模型支撑地理分析与建模的关键.本文基于多粒度时空对象建模理论,在概率图和条件概率表的基础上发展了一种基于Bayes网络的地理...     

基于模糊影响图的海洋结构风险分析方法研究

基于模糊影响图(FPID)和失效模式与效果分析(FMEA)建立了一种海洋结构风险分析方法。鉴于风险分析中某些事件发生概率和关系概率两个重要参数确定时需借助专家主观判断,本文将模糊概率的概念引入海洋结构影响图评估方法中。该方法成功地应用到海洋平台人员伤害分析中。虽然这里仅给出了该方法在海洋平台风险评估中的应用,但其具有更广泛应用价值。     

Rocking amplification and strong‐motion duration

This paper characterizes the ability of natural ground motions to induce rocking demands on rigid structures. In particular, focusing on rocking blocks of different size and slenderness subjected to a large number of historic earthquake records, the study unveils the predominant importance of the strong‐motion duration to rocking amplification (ie, peak rocking response without overturning). It proposes original dimensionless intensity measures (IMs), which capture the total duration (or total impulse accordingly) of the time intervals during which the ground motion is capable of triggering rocking motion. The results show that the proposed duration‐based IMs outperform all other examined (intensity, frequency, duration, and/or energy‐based) scalar IMs in terms of both “efficiency” and “sufficiency.” Further, the pertinent probabilistic seismic demand models offer a prediction of the peak rocking demand, which is adequately “universal” and of satisfactory accuracy. Lastly, the analysis shows that an IM that “efficiently” captures rocking amplification is not necessarily an “efficient” IM for predicting rocking overturning, which is dominated by the velocity characteristics (eg, peak velocity) of the ground motion.