福建及其周边地区地震活动人工神经网络模型的构建

本文通过对福建及其周边地区地震活动人工神经网络模型的构建,研究了人工神经网络方法在基于该区域地震活动性指标的地震分析预报中的应用。选用含一个中章层的前向神经网络模型,并采用与之相适应的ＢＰ算法,以该地区１９７１～１９９７年的地震活动性资料为基础,用神经网络进行实际计算、分析和检验。结果表明：神经网络模型对福建及其周边地区地震震级的预测检验效果较好的,可以在一定精度范围内使震级预测的内符率达１００％     

状态转移矩阵的差分算法及其应用

指出用数值积分方法计算状态转移矩阵在程序实现时存在的困难。根据精密定轨和参数解算的实际需要,提出用差分算法,即通过两条接近的轨道的差来计算状态转移矩阵差分算法的优点是程序具有良好的结构且编程简单,其不足之处是差分时可能损失精度。将差分算法与数值积分方法的结果进行比较,提出克服其不足处的方法。     

Geocentre motion from the DORIS space system and laser data to the Lageos satellites: comparison with surface loading data

Surface mass redistribution within the Earth system, especially in the atmosphere, oceans, continents and ice sheets, causes the position of the centre of mass to vary in a reference frame attached to the solid Earth. Space techniques are now precise enough to measure the centre of mass motion. Here we present a determination of the centre of mass coordinates at regular monthly intervals using DORIS data on SPOT‐2, SPOT‐3 and Topex–Poseidon (1993–1997) and laser data on Lageos‐1 and Lageos‐2 (1993–1996). The amplitude and phase of the space‐geodesy‐derived annual cycle for each coordinate are further compared to estimates based on surface mass redistribution at the Earth surface derived from various climatic data sources: surface pressure, soil moisture, snow depth and ocean mass variations.     

An anomalous high-velocity layer at shallow crustal depths in the Narmada zone, India

The Narmada zone in central India is a zone of weakness that separates the region of Vindhyan (Meso-Neoproterozoic) deposition to the north from Gondwana (Permo-Carboniferous–lower Cretaceous) deposits to the south. The reinterpretation of analogue seismic refraction data, acquired during the early 1980s, using 2-D ray-tracing techniques reveals a basement (velocity 5.8–6.0 km s⁻¹ ) topography suggesting that the Narmada zone, bounded by the Narmada North and Narmada South faults is a region of basement uplift. A layer of anomalously high velocity (6.5–6.7 km s⁻¹ ) at depths between 1.5 and 9.0 km appears to be present in the entire region. Within the Narmada zone this layer occurs at shallower depths than outside the Narmada zone. At two places within the Narmada zone this layer is at a depth of about 1.5 km. This layer cannot be considered as the top of the lower crust because in this case it should have produced large positive gravity anomalies at the shallowest parts. Instead, these parts correspond to Bouguer gravity lows. Furthermore, lower crust at such shallow depths has not been reported from any other part of the Indian shield. Therefore, this layer is likely to represent the top of a high-velocity mafic body that has different thicknesses in different places.     

梯级-关联算法原理及其在月流量预报中的应用

传统BP网络需要预先设定网络隐含层的层数和每层的节点数,使得在预测过程中难以确定网络的最优结构。与之相反,梯级-关联算法(CC)要求初始网络仅含有输入层和输出层,通过运算不断向网络增加隐含节点。在介绍梯级-关联算法原理的基础上,分别运用梯级-关联算法和BP算法对拉萨河拉萨站的月流量进行了预测,结果显示:在不损失预测精度的前提下,梯级-关联算法的运算次数仅为5次,而BP算法则需要运算70 000次,运算效率有很大的提高,同时网络的规模也有所减小。     

水库控制流域汛期分期的有效聚类分析

受诸多因素影响的水库汛期分期其实质是一个聚类数目未确知的高维时间序列聚类问题,它要求聚类方法具有能处理高维和时序性数据,且能同时回答聚为几类最为合理的能力。鉴于目前常规聚类方法不同时具备这些能力,在模糊C-均值聚类和紧密与分离聚类有效函数的基础上,提出了能够处理高维时序聚类问题的动态模糊C-均值聚类分析方法和相应的时序聚类有效性函数,耦合二者建立了适用于汛期分期的有效模糊聚类分析方法,提出采用实码加速遗传算法优化求解,克服了模糊C-均值聚类方法常规迭代优化求解对初值敏感的困难,并给出了完备的建模步骤和模型的合理性检验。最后,将模型应用于滦河流域潘家口水库汛期分期中,得出了合理的结论。     

A high precision comprehensive evaluation method for flood disaster loss based on improved genetic programming

Precise comprehensive evaluation of flood disaster loss is significant for the prevention and mitigation of flood disasters. Here, one of the difficulties involved is how to establish a model capable of describing the complex relation between the input and output data of the system of flood disaster loss. Genetic programming （GP） solves problems by using ideas from genetic algorithm and generates computer programs automatically. In this study a new method named the evaluation of the grade of flood disaster loss （EGFD） on the basis of improved genetic programming （IGP） is presented （IGP-EGFD）. The flood disaster area and the direct economic loss are taken as the evaluation indexes of flood disaster loss. Obviously that the larger the evaluation index value, the larger the corresponding value of the grade of flood disaster loss is. Consequently the IGP code is designed to make the value of the grade of flood disaster be an increasing function of the index value. The result of the application of the IGP-EGFD model to Henan Province shows that a good function expression can be obtained within a bigger searched function space; and the model is of high precision and considerable practical significance. Thus, IGP-EGFD can be widely used in automatic modeling and other evaluation systems.     

透射射线的非线性效应

根据Snell定律提出了透射射线的非线性效应的概念,从理论上证明了当地震射线的轨迹在1个界面上为1条直线时在另1个界面上可为1条曲线;并进一步通过射线追踪实验证明:当地下介质为非水平层状介质时,即使对应于地面同一条直线段上的接收点,来自地下同一个界面上的反射点的轨迹仍可为一条曲线。     

一种新型混沌遗传优化算法的研究

在对遗传算法交叉、变异后结果的处理方法进行改进并在将进化过程分段的基础上,提出1种新的混沌遗传算法。该算法利用混沌运动的遍历性择优产生初始群体,对每一轮遗传操作所得到的部分当前最优个体进行变尺度混沌搜索。仿真结果表明,该算法具有较高的优化效率,并能求得全局最优解。     

自适应遗传算法配准三维数字样品模型及其CAD模型

通过包围盒的初始匹配和浮点数编码自适应遗传算法的精确匹配,实现了三维数字样品模型及其CAD模型的配准。初始匹配决定精确匹配空间变换参数的范围;精确匹配在搜索变换矩阵的6个变换参数过程中,采用最小二乘方法构造目标函数;遗传算法中引入种群多样性指标;在遗传操作的交叉算子和变异算子中引入该指标,并将该指标用于交叉概率和变异概率两个参数的调整,有效地克服了遗传算法的早收敛问题。实验结果表明该方法较好地解决了三维数字样品模型及其CAD模型的配准问题,且算法稳定,易于实现。