近45 a东北地区春季降水异常的气候特征

利用1959-2003年我国东北地区93站春季降水资料，将降水场分成5个区域，并在此基础之上分析了春季降水的时空变化特征，发现：降水量年际变化及长期趋势有明显的区域差异，呈东多西少的分布特征；西部是旱涝易发生区，近45a来降水量略有增多；降水量的周期振荡存在明显的区域差异。     

多矿物岩石流变规律的研究进展及存在问题

总结了近年来由多种矿物组成的岩石的流变规律的研究，阐述了多矿物岩石流变性质研究的意义和进展，再从实验和理论两个方面，详细论述了目前最具代表性的三种理论模型，算术平均方法、几何平均方法和能量极小方法，最后，指出这方面研究仍然存在的问题和进一步研究的方向。     

中国重力异常的小波变换与多尺度分析

阐述了小波变换及多尺度分析方法的原理，利用二维小波多尺度分析方法对中国布格重力异常进行了分解，并从其中划分出有意义的剩余异常．模型结果证明方法有效．由于本文方法可以将重力异常分解成各种几何尺度意义下的不同成分，这为重力解释和研究地壳的结构提供更多更新的依据．     

Simulation of normal distributed smooth fields by Karhunen-Loéve expansion in combination with kriging

Simulation of multigaussian stochastic fields can be made after a Karhunen-Loéve expansion of a given covariance function. This method is also called simulation by Empirical Orthogonal Functions. The simulations are made by drawing stochastic coefficients from a random generator. These numbers are multiplied with eigenfunctions and eigenvalues derived from the predefined covariance model. The number of eigenfunctions necessary to reproduce the stochastic process within a predefined variance error, turns out to be a cardinal question. Some ordinary analytical covariance functions are used to evaluate how quickly the series of eigenfunctions can be truncated. This analysis demonstrates extremely quick convergence to 99.5% of total variance for the 2nd order exponential (‘gaussian’) covariance function, while the opposite is true for the 1st order exponential covariance function. Due to these convergence characteristics, the Karhunen-Loéve method is most suitable for simulating smooth fields with ‘gaussian’ shaped covariance functions. Practical applications of Karhunen-Loéve simulations can be improved by spatial interpolation of the eigenfunctions. In this paper, we suggest interpolation by kriging and limits for reproduction of the predefined covariance functions are evaluated.     

Simulation of normal distributed smooth fields by Karhunen-Loéve expansion in combination with kriging

Simulation of multigaussian stochastic fields can be made after a Karhunen-Loéve expansion of a given covariance function. This method is also called simulation by Empirical Orthogonal Functions. The simulations are made by drawing stochastic coefficients from a random generator. These numbers are multiplied with eigenfunctions and eigenvalues derived from the predefined covariance model. The number of eigenfunctions necessary to reproduce the stochastic process within a predefined variance error, turns out to be a cardinal question. Some ordinary analytical covariance functions are used to evaluate how quickly the series of eigenfunctions can be truncated. This analysis demonstrates extremely quick convergence to 99.5% of total variance for the 2nd order exponential (‘gaussian’) covariance function, while the opposite is true for the 1st order exponential covariance function. Due to these convergence characteristics, the Karhunen-Loéve method is most suitable for simulating smooth fields with ‘gaussian’ shaped covariance functions. Practical applications of Karhunen-Loéve simulations can be improved by spatial interpolation of the eigenfunctions. In this paper, we suggest interpolation by kriging and limits for reproduction of the predefined covariance functions are evaluated.     

甘肃省东南部未来地震危险区的模式识别

在综合分析甘肃省东南部地震地质特征的基础上，利用模式识别方法判定未来地震危险区的可能位置．结果表明，本区易发生地震的地点与全新世断裂强烈活动段相吻合，从而提高了对未来地震危险区判定的可信度     

Proposed support design, Kaletepe tunnel, Turkey

In this paper, preliminary support design of Kaletepe tunnel, located on Bilecik-Istanbul highway, Turkey, was analyzed by empirical and numerical methods. The rock mass rating (RMR) and rock mass quality (Q) systems were employed for empirical rock mass quality determination. Numerical analysis for the stress–strain distribution of the tunnel excavation and support systems was also carried out. The applied support performance was investigated at different sections of the tunnel route. It was seen that empirical and numerical approaches showed similar results. This indicates that when the empirical method is supported by numerical method, the preliminary support design will be more reliable.     

腐解9个月后杉木枯枝落叶化感物质对杉木的化感作用

采用有机溶剂与蒸馏水混和浸提杉木枯枝落叶腐解9个月后化感物质,应用杉木种子发芽试验进行生物检测.结果表明:杉木枯枝落叶腐解9个月后,杉木枯枝落叶中的弱极性化感物质对绝对发芽率、绝对发芽势、胚根长、胚轴长及干物质量等指标表现为抑制作用,对鲜物质量则表现为轻微的促进作用;极性化感物质对杉木种子发芽各指标均等表现为抑制作用.腐解土中的弱极性化感物质对杉木种子发芽各指标均表现为抑制作用,极性化感物质对绝对发芽率、绝对发芽势、胚轴长及干物质量等表现为抑制作用,但对胚根长、鲜物质量表现为促进作用.     

基于EEMD和ARIMA的海温预测模型研究

类型丰富、时空分辨率高的海洋探测数据,为信号分解和机器学习算法的应用提供了可能。本文针对如何建立有效的海温预测模型这一问题,使用高时空分辨率的海表温度(SST)融合产品,引入信号处理领域的集合经验模态分解(EEMD)和机器学习领域的自回归积分滑动平均模型(ARIMA)。首先利用最适于分解自然信号的EEMD方法,将海温数据分解成多个确定频率的序列;再利用ARIMA分别对各个频率的序列进行预测,最后将各个序列的预测结果进行组合。该方法在丰富数据的支撑下,比以往直接使用海温数据所建立的预测模型精度更高,为更好地进行海温预测提供了新方法。     

Research on the Method of De-noising the Short-wave Time Signal at Low SNR

A voice enhancement algorithm based on the Empirical Mode Decomposition (EMD) and the improved spectral subtraction is proposed for the low-SNR (Signal Noise Ratio) shortwave time signal. This method is proposed to solve the problem that the shortwave time signal cannot be used for timing in complex noisy environments. The core idea of this method is to use the Hilbert-Huang Transform (HHT) algorithm to make the empirical mode decomposition on the noisy shortwave signal, and to select the intrinsic mode functions containing the shortwave signal information for the signal reconstruction by through the maximum correlation. Then, to make the spectral subtraction on the reconstructed signal to achieve the purpose of noise reduction. The experimental result shows that this method has a better noise reduction than the traditional methods.