地震空间分维Dq及b值的临震变化特征及其非线性机制分析

对云南省几个不同地区的强震孕震阶段及临震时的地震空间分维Ｄｑ（ｑ＝０，１，２，）及ｂ值进行了计算和研究，发现虽然在孕震阶段各地区的Ｄｑ及ｂ值均有着共同的下降主趋势，但临震时不同区域的Ｄｑ及ｂ的变化形态却存在着差异，大地震可能发生在Ｄｑ及ｂ值均降至最低时，也可能发生在Ｄｑ及ｂ值下降后又回升之时，还可能发生在Ｄｑ回升而ｂ值仍保持最低时。本着重对Ｄｑ及ｂ值的临震变化特征及其个体差异从非线性的角度作了物     

前兆异常的非线性识别与地震危险地点的判定

利用多种描述复杂现象的非线性方法处理了多台多项多年的前兆观测资料，通过“场”、“源”特征差异性的对比求得地震危险地点是一个能量“振荡”型积累的地区，具体表现为它是在前兆异常演化过程中出现的异常从属度最高、自相似性变化最大、前兆分维数下降最多的地区，而且还是在地震活动过程中出现的一个熵值相对较低的地区。研究结果还表明，震中位置的不确定性随着发震时刻的逼近而不断减弱     

对称化测量高频电磁波测井的优化组合研究

采用对称化测量可克服现有单发双收高频电磁波测井仪器（ＤＰＴ）由于收－发不对称结构导致的幅度比测井曲线严重失真的缺陷，提高ＤＰＴ的纵向分辨率．通过对二线非均质测井环境下ＤＰＴ响应的数值模拟，指出选用原频率较低、源距较长仪器的相位差测量与源频率较高、源距较短仪器的幅度比测量进行组合，可获得高品质的视介电常数和视电阻率曲线，显著提高ＤＰＴ的资料解释能力．这里源频率的恰当选择起着关键作用．     

强震地面运动的解析解

本文用具有非线性Ｒａｙｌｅｉｇｈ阻尼的断裂动力学的控制方程组或方程来研究水平强震地面运动或垂直强震地面运动，并得出其解析解，数值计算结果显示，本文得出的结果与任意选择的两个强震记录是很相似的。     

山地降水垂直分布三参数高斯模式及其应用

针对蒋忠信山地降水高斯模式计算中的问题,提出三参数高斯模式及其非线性回归计算方法,将其应用于我国部分山地降水中,效果较好。     

地震前兆异常时间分布非线性特征的初步探讨——以海城地震和唐山地震为例

震源系统是一个与外界既有物质交换又有能量交换的耗散系统,在其发展演化过程中会经历一系列的分岔突变。作者运用非线性动力学的方法,分析了海城地震和唐山地震的前兆资料。研究结果表明,前兆异常活动具有阶段性,相邻两个异常阶段的持续时间的比值为一常量(5左右)。这种前兆时间分布规律可用震源体内应变能密度随孕震时间的增加发生倍周期分岔进行解析。它可用于预测主震的发生时间     

A study on the nonlinear stability of fronts in the ocean on a sloping continental shelf

1.IntroductionArnol'd(1965,1969)variationalprincipleandapriorestimatemethodisessentiallyageneralizationofLyapunovstabilitymethodforfinite--dimensionaldynamicalsystemsininfinite--dimensionalones,andhestudiedthenonlinearstabilityof2--dimensionalincompressibleidealfluidmotionbyuseofthismethod,andestablishedtwotheoremswhichareArnol,d'sfirsttheoremandArnol'd'ssecondtheorem.Eversincethe1980's,manyscientistshavebeenworkingonthissubject,Holmetal.(1985);MclntyreandShepherd(1987);Zeng(1989);Muetal.(1…     

Improving the efficiency of ant algorithms using adaptive refinement: Application to storm water network design

The ant algorithm is a new evolutionary optimization method proposed for the solution of discrete combinatorial optimization problems. Many engineering optimization problems involve decision variables of continuous nature. Application of the ant algorithm to the optimization of these continuous problems requires discretization of the continuous search space, thereby reducing the underlying continuous problem to a discrete optimization problem. The level of discretization of the continuous search space, however, could present some problems. Generally, coarse discretization of the continuous design variables could adversely affect the quality of the final solution while finer discretization would enlarge the scale of the problem leading to higher computation cost and, occasionally, to low quality solutions. An adaptive refinement procedure is introduced in this paper as a remedy for the problem just outlined. The method is based on the idea of limiting the originally wide search space to a smaller one once a locally converged solution is obtained. The smaller search space is designed to contain the locally optimum solution at its center. The resulting search space is discretized and a completely new search is conducted to find a better solution. The procedure is continued until no improvement can be made by further refinement. The method is applied to a benchmark problem in storm water network design discipline and the results are compared with those of existing methods. The method is shown to be very effective and efficient regarding the optimality of the solution, and the convergence characteristics of the resulting ant algorithm. Furthermore, the method proves itself capable of finding an optimal, or near-optimal solution, independent of the discretization level and the size of the colony used.