中国高放废物处置库选址中灵敏地质特征的初步确认

本文首先根据中国、瑞士和日本3国高放废物处置概念的相似性，建立中国第一处置库系统性能评价模型；然后通过对9个地质变量在8个事件中的灵敏度分析，初步确认出3个灵敏地质物征。此项研究对中国目前高放废物处置库选址工作有一定的指导意义。     

Neuro‐control of seismically excited steel structure through sensitivity evaluation scheme

The neuro‐controller training algorithm based on cost function is applied to a multi‐degree‐of‐freedom system; and a sensitivity evaluation algorithm replacing the emulator neural network is proposed. In conventional methods, the emulator neural network is used to evaluate the sensitivity of structural response to the control signal. To use the emulator, it should be trained to predict the dynamic response of the structure. Much of the time is usually spent on training of the emulator. In the proposed algorithm, however, it takes only one sampling time to obtain the sensitivity. Therefore, training time for the emulator is eliminated. As a result, only one neural network is used for the neuro‐control system. In the numerical example, the three‐storey building structure with linear and non‐linear stiffness is controlled by the trained neural network. The actuator dynamics and control time delay are considered in the simulation. Numerical examples show that the proposed control algorithm is valid in structural control. Copyright © 2001 John Wiley & Sons, Ltd.     

计算机仿真模型的灵敏度分析

计算机仿真模型的灵敏度分析，是仿真建模中的重要研究内容，对实际系统的建立和优化具有重要意义。本文主要研究了在用蒙特卡洛方法仿真随机系统时，其仿真模型（输出）的灵敏度（导数、梯度、Ｈｅｓｓｉａｎ矩阵等），对系统性能函数和灵敏度的参数估计进行了探讨，并结合实际应用系统，对结论进行了分析比较。     

关于垂直分量磁变仪的灵敏度问题

目前国内地磁台垂直分量磁变以的灵敏度都普遍偏低，不能适应一些研究工作的需要，必须予以适当的提高，本文在基本不改变仪器固有灵敏度的前提下，采取记录光线二次反射法，以提高仪器的记录灵敏度，利用这种方法既使仪器的灵敏度提高一倍同时又保证了仪器原有的稳定性。     

Effects of magnitude accuracy and complete－ness data on seismic hazard parameters

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A NEW QUANTITATIVE WAY FOR DETERMINING LEAF AREA INDEXAND NET PRIMARY PRODUCTIVITY IN REGIONAL SCALE

IntroductionThemaJorpurposeforremotesensingistoobtuinqUantitativevaluabledrirmationonvanousaPplicahons.PanicularlybiophysicalparametersinwionalandglobalscaleareofintereSttoanumberofdomams.ForinStancem,croPyteldestiInatinleafareaindex,chiorophyllcontentandheightofcroparecruaalindex.EvaPotranSirationinroponalscalenedstogctdistnbtaloninformationofcrophdghttoinferrowiessOfsuffoceandsoon.AsthoopthenormaldifferenceVegetaonindex(NDVI)hasbecameaverypoPularmethodtoeinmateLAI,therelationshipbet…     

电感应力灵敏度在实测中的研究

应力场的观测是预报地震较直接的途径之一,本实验利用异孔深井抽水的加(减)载作应力观测的人工力源,在大量实测数据基础上进行力学分析,得出电感应力观测在满足规范要求时能测到地应力场的变化,但室内标定的应力灵敏度不等于实测灵敏度。用室内灵敏度计算应力值必有明显误差。本结果对电惑应力观测科学具有重要的实际意义。     

大型抽水试验最优化设计研究

抽水试验最优化设计,是指针对一个具体的地下水系统优选出一个抽水试验设计,它使抽水试验的费用最小化,而试验所获资料能满足识别参数所要求的可靠性,它可以概化为一个非线性的混合整数规划问题,其决策变量是确定抽水井和观测井的位置及井数、抽水量和观测频率等,采用搜索算法求解了这一优化问题,得到了理论最优解,并进行了实例演算。     

Estimating Petroleum Resources Using Geo-Anchored Method--A Sensitivity Study

The Geo-anchored method, based on a moment-type estimator, has been developed for estimating parent population properties from a successive sample of discoveries. By substituting the expectation of the waiting time z _(n+1) of the (n + 1) ^th discovery to occurrence for an unknown parameter in the anchored method, the Geo-anchored method allows estimation of inclusion probabilities directly from observed data, thus eliminating the need for a priori selection of a value of N, R, or some other feature of the parent population. Because direct estimation of N and R requires an ordered sample, the Geo-anchored method is more sensitive to the data-generating process than the anchored method. This paper presents a sensitivity study on the Geo-anchored method. The test is based on simulated discovery sequences with different assumptions regarding discovery efficiency, exploration maturity, and the shape of the parent field size distribution. As a reference for comparison, estimates from the Horvitz–Thompson estimator also are presented.     

Species sensitivity distributions: data and model choice

Species sensitivity distributions (SSDs) are increasingly incorporated into ecological risk assessment procedures. Although these new techniques offer a more transparent approach to risk assessment they demand more and superior quality data. Issues of data quantity and quality are especially important for marine datasets that tend to be smaller (and have fewer standard test methods) when compared with freshwater data. An additional source of uncertainty when using SSDs is appropriate selection from the range of methods used in their construction. We show through examples the influence of data quantity, data quality, and choice of model. We then show how regulatory decisions may be affected by these factors.