新疆地震预报研究

新疆的地震预报是1970年开始的。二十多年来在“边观测、边研究、边预报”、“多路探索、多兵种联合作战”、“走综合预报之路”的方针指导下取得了长足的进展。建设了43个地震台站,投入189套仪器,建成了遍布全疆的地震无线通讯网,开展了历史地震调查和地震烈度区划工作,建立健全了地震会商预报制度,进行了多方面的地震预报研究。实际地震预报统计分析表明,扣除自然发震概率之后,趋势预报的成功率约0.3,短临预报的成功率约0.1。在前兆台网控制范围内取得了一些震例,说明地震确实是有前兆的,但又是非常复杂的。地震预报作为科学难题还有漫长的路要走。作者简要地讨论了地震观测的间接性和地震异常的离散性、难以区别的地震异常和地壳变动异常、建立在复杂现象基础上的地震前兆以及地震的混沌性对地震预报的影响等科学问题。     

基于改进PSO-SVM的噪声稳健建筑物变形监测方法

对高层、超高层建筑物进行实时,高精度的变形监测对提前预防安全隐患,保证人民生命财产安全具有重要意义。建筑物变形作为一种典型的随机性和微弱性过程,噪声等误差的存在会影响从中提取有用的变形信息。针对该问题,提出一种改进粒子群(Particle Swarm Optimization,PSO)算法优化支持向量机(Support Vector Machine,SVM)的噪声稳健建筑物变形监测方法,利用改进PSO算法的全局搜索能力对SVM的核参数进行优化,提升预测精度的同时增强算法的噪声稳健性。基于实测数据的试验结果表明,相对于传统交叉验证SVM和小波方法,所提方法可以获得更高的变形预测精度,并且在低信噪比条件下优势更加明显。     

Estimation for partially observed Markov processes

Many stochastic process models for environmental data sets assume a process of relatively simple structure which is in some sense partially observed. That is, there is an underlying process (X_n, n 0) or (X_t, t 0) for which the parameters are of interest and physically meaningful, and an observable process (Y_n, n 0) or (Y_t, t 0) which depends on the X process but not otherwise on those parameters. Examples are wide ranging: the Y process may be the X process with missing observations; the Y process may be the X process observed with a noise component; the X process might constitute a random environment for the Y process, as with hidden Markov models; the Y process might be a lower dimensional function or reduction of the X process. In principle, maximum likelihood estimation for the X process parameters can be carried out by some form of the EM algorithm applied to the Y process data. In the paper we review some current methods for exact and approximate maximum likelihood estimation. We illustrate some of the issues by considering how to estimate the parameters of a stochastic Nash cascade model for runoff. In the case of k reservoirs, the outputs of these reservoirs form a k dimensional vector Markov process, of which only the kth coordinate process is observed, usually at a discrete sample of time points.     

Reservoir description using dynamic parameterisation selection with a combined stochastic and gradient search

There is a correspondence between flow in a reservoir and large scale permeability trends. This correspondence can be derived by constraining reservoir models using observed production data. One of the challenges in deriving the permeability distribution of a field using production data involves determination of the scale of resolution of the permeability. The Adaptive Multiscale Estimation (AME) seeks to overcome the problems related to choosing the resolution of the permeability field by a dynamic parameterisation selection. The standard AME uses a gradient algorithm in solving several optimisation problems with increasing permeability resolution. This paper presents a hybrid algorithm which combines a gradient search and a stochastic algorithm to improve the robustness of the dynamic parameterisation selection. At low dimension, we use the stochastic algorithm to generate several optimised models. We use information from all these produced models to find new optimal refinements, and start out new optimisations with several unequally suggested parameterisations. At higher dimensions we change to a gradient-type optimiser, where the initial solution is chosen from the ensemble of models suggested by the stochastic algorithm. The selection is based on a predefined criterion. We demonstrate the robustness of the hybrid algorithm on sample synthetic cases, which most of them were considered insolvable using the standard AME algorithm.     

Temporal behavior of the background seismicity rate in central Japan, 1998 to mid-2003

We studied the temporal behavior of the background shallow seismicity rate in 700 circular areas across inland Japan. To search for and test the significance of the possible rate changes in background seismicity, we developed an efficient computational method that applies the space–time ETAS model proposed by Ogata in 1998 to the areas. Also, we conducted Monte Carlo tests using a simulated catalog to validate the model we applied. Our first finding was that the activation anomalies were found so frequently that the constant background seismicity hypothesis may not be appropriate and/or the triggered event model with constraints on the parameters may not adequately describe the observed seismicity. However, quiescence occasionally occurs merely by chance. Another outcome of our study was that we could automatically find several anomalous background seismicity rate changes associated with the occurrence of large earthquakes. Very significant seismic activation was found before the M6.1 Mt. Iwate earthquake of 1998. Also, possible seismic quiescence was found in an area 150 km southwest of the focal region of the M7.3 Western Tottori earthquake of 2000. The seismicity rate in the area recovered after the mainshock.     

角度格式转换过程中可靠算法研究

提出了一种可靠算法是将原始度.分秒加上一个与之同符号,且不影响计算精度的有效微小量ｅ,然后再进行格式转换,能有效减少工程返工和损失。     

基于可分解马尔科夫网的极端椒盐噪声图像滤波

提出了一种基于可分解马尔科夫网(decomposableMarkovnetworks,DMN)的极端椒盐噪声的均值滤波方法,指出其网络节点的阈值衰减特性和网络节点的连接特性具有很好的对椒盐噪声污染图像的噪声定位的作用,并提出一种在该网络控制下,只对与噪声相关的像素进行均值计算以替代噪声像素的亚均值滤波算法,实现了图像的较强自适应滤波。实验表明,本文方法具有良好的滤波性能。     

C1相干算法及其在三维地震资料处理解释中的应用

C1相干算法是计算每道的横测线和相邻纵测线的互相关，依据相干值来判断地层和岩性的横向不均匀性。根据互相关原理，提出了相干体算法中二维和三维C1算法的内容及其具体实现。通过对实际三维地震资料的处理，结合已知地质资料，证明C1相干技术在三维地震资料的断层解释方面有着明显的效果。     

方差体技术在地震勘探中的应用

三维地震数据体反映了地下一个规则网格的反射情况。当遇到地下有断层或某个局部区域地层不连续变化时，一些地震道的反射特征就会与附近地震道出现差异而导致地震首局部的不连续性。三维方差体技术就是求取三维数据体所有样点的方差值来反映这种不连续性信息。通过该技术在济宁2号井某采区的实际应用，可看出，方差体技术在三维地震信息的自动拾取以及提高地震资料解释成果精度等方面有明显优势，对断层、陷落柱有良好的自动识别能力。