变形监测信息管理系统的设计与实现

介绍了GIS数据管理与图形显示的优势、组件技术,设计了变形监测数据管理系统平台,实现了变形监测数据的智能化管理、分析与预测.     

矿井涌水量混沌时间序列分析与预测

矿井地下水系统是个非线性系统,由于地下水系统的复杂性,很难完全确定影响矿井涌水量的因素,因此传统的矿井涌水预测表现出较大的局限性。而混沌时间序列分析能够利用单变量处理方法,分析矿井地下水系统中,由于多因素耦合作用所产生的矿井涌水量时间序列。通过对某矿区1985年9月至2005年2月矿井涌水量时间序列资料的分析,显示矿井涌水量时间序列具有混沌特征;通过对比预测值和实测值,表明预测精度高。因此,混沌时间序列分析方法用于矿井涌水量预测是可行的。     

Prediction of UT1–UTC,LOD and AAM χ<Subscript>3</Subscript> by combination of least-squares and multivariate stochastic methods

This article presents the application of a multivariate prediction technique for predicting universal time (UT1–UTC), length of day (LOD) and the axial component of atmospheric angular momentum (AAM χ ₃). The multivariate predictions of LOD and UT1–UTC are generated by means of the combination of (1) least-squares (LS) extrapolation of models for annual, semiannual, 18.6-year, 9.3-year oscillations and for the linear trend, and (2) multivariate autoregressive (MAR) stochastic prediction of LS residuals (LS + MAR). The MAR technique enables the use of the AAM χ ₃ time-series as the explanatory variable for the computation of LOD or UT1–UTC predictions. In order to evaluate the performance of this approach, two other prediction schemes are also applied: (1) LS extrapolation, (2) combination of LS extrapolation and univariate autoregressive (AR) prediction of LS residuals (LS + AR). The multivariate predictions of AAM χ ₃ data, however, are computed as a combination of the extrapolation of the LS model for annual and semiannual oscillations and the LS + MAR. The AAM χ ₃ predictions are also compared with LS extrapolation and LS + AR prediction. It is shown that the predictions of LOD and UT1–UTC based on LS + MAR taking into account the axial component of AAM are more accurate than the predictions of LOD and UT1–UTC based on LS extrapolation or on LS + AR. In particular, the UT1–UTC predictions based on LS + MAR during El Niño/La Niña events exhibit considerably smaller prediction errors than those calculated by means of LS or LS + AR. The AAM χ ₃ time-series is predicted using LS + MAR with higher accuracy than applying LS extrapolation itself in the case of medium-term predictions (up to 100 days in the future). However, the predictions of AAM χ ₃ reveal the best accuracy for LS + AR.     

动态最小二乘支持向量机学习算法

针对大样本集的训练问题和动态训练样本的模型更新问题,提出了动态最小二乘支持向量机学习算法.该算法充分利用已建好的模型,逐渐加入新样本,并可删除位于任何位置的非支持向量,避免了矩阵求逆运算,保证了算法的高效率.大坝变形及电离层延迟两个时间序列的预报实例表明,该算法具有计算时间短、预报精度高的特点.     

Extension of the solution of Kepler's equation to high eccentricities

The classic Lagrange's expansion of the solutionE(e, M) of Kepler's equation in powers of eccentricity is extended to highly eccentric orbits, 0.6627 ... <e<1. The solutionE(e, M) is developed in powers of (e–e*), wheree* is a fixed value of the eccentricity. The coefficients of the expansion are given in terms of the derivatives of the Bessel functionsJ _n (ne). The expansion is convergent for values of the eccentricity such that |e–e*|<(e*), where the radius of convergence (e*) is a positive real number, which is calculated numerically.     

Long-term prediction of intermediate depth earthquakes in the southern Aegean region based on a time-predictable model

Repeat times of strong intermediate depth (60 km h 180 km) earthquakes have been determined by the use of instrumental and historical data for six seismogenic sources in the Benioff zone of the southern Aegean area. For four of these sources, at least two interevent times (three mainshocks) are available for each source. By using the repeat times for these four sources, the following relation has been determined: logT _t = 0.20M _min + 0.19M _p +a, whereT _t is the repeat time (in years),M _min the surface wave magnitude of the smallest earthquake considered,M _p the magnitude of the preceding mainshock and a parameter which varies from source to source. A multilinear correlation coefficient equal to 0.91 was determined for this relation, which indicates that the time predictable model holds to a satisfactory degree for the strong mainshocks of intermediate focal depth in the southern Aegean.By assuming that the ratioT/T _t, whereT is the observed andT _t the calculated repeat time, follows a lognormal distribution, the conditional probabilities for the occurrence of strong (M _s 6.5) and very strong (M _s 7.5) earthquakes during the period 1991–2001 in these four seismogenic sources have been calculated. These probabilities are very high (P > 0.9) for the strong and high (P > 0.5) for the very strong intermediate depth earthquakes which occur in the three sources of the shallower (h < 100 km) part of the Benioff zone where coupling occurs between the front parts of the Mediterranean lithosphere (downgoing) and the Aegean lithosphere.     

System for normalization of a hamiltonian function based on lie series

A software system for normalization of a Hamiltonian function is described. A few examples of its applications are given. It is written in PASCAL and runs on an IBM XT/AT with 640 KB memory.     

Testing earthquake prediction methods: «The West Pacific short-term forecast of earthquakes with magnitude MwHRV ≥ 5.8»

Analyzing the tables and probability maps posted by Yan Y. Kagan and David D. Jackson in April 2002–September 2004 at http://scec.ess.ucla.edu/~ykagan/predictions_index.html and the catalog of earthquakes for the same period, the conclusion is drawn that the underlying method could be used for prediction of aftershocks, while it does not outscore random guessing when main shocks are considered.     

Modeling the cyclic swelling pressure of mudrock using artificial neural networks

The stochastic nature of the cyclic swelling behavior of mudrock and its dependence on a large number of interdependent parameters was modeled using Time Delay Neural Networks (TDNNs). This method has facilitated predicting cyclic swelling pressure with an acceptable level of accuracy where developing a general mathematical model is almost impossible. A number of total pressure cells between shotcrete and concrete walls of the powerhouse cavern at Masjed–Soleiman Hydroelectric Powerhouse Project, South of Iran, where mudrock outcrops, confirmed a cyclic swelling pressure on the lining since 1999. In several locations, small cracks are generated which has raised doubts about long term stability of the powerhouse structure. This necessitated a study for predicting future swelling pressure. Considering the complexity of the interdependent parameters in this problem, TDNNs proved to be a powerful tool. The results of this modeling are presented in this paper.     

Reliability Based Assessment of Shallow Foundations Using Mathcad

A reliability based method was used to design and analyse shallow foundations using first-order Taylor series approximation. The computer program Mathcad was used to facilitate all mathematical and computional efforts. This method is an effective tool to assist the foundation designers and analyists to investigate how reliable their designs or analyses are in relation to the ultimate bearing capacity of the foundations. The approach presented in this paper provides a reliable alternative for design and analysis of shallow foundations, rather than the conventional design methods, which employs the assumptions of a specified saftey factor. Several examples were presented for design and analysis of strip footings embedded in sandy soil, and rectangular and square footings analysis embedded in clayey soils. The program input and output of each example are also presented and discussed.