抗洪抢险措施及效果

结合“９８”抗洪抢险实例，对多种险情作了具体分析，通过汛后调查，对抗洪抢险消险措施和效果进行了总结，为今后进一步做好防洪消险工作提供了经验。     

暴雨洪水流域系统随机模拟(研究之三)

本文提出的移置特大暴雨的不连序序列的随机插补方法,以及利用W—H逆变换法将偏态暴雨序列转为正态序列和随机扣除模拟的暴雨过程损失量等方法,基本是可行的,对提高模型的代表性、稳定性和实用性有重要作用。     

脱除重油中有害金属杂质新技术

用化学药剂在一定条件下进行反应后用水萃取，并用 电脱水的方法脱除金属.研究了注药剂量、反应温度和反应时间等因素对脱除率的影响.     

RECURSIVE GENERALIZED M ESTIMATES FOR AUTOREGRESSIVE MOVING-AVERAGE MODELS

Abstract. Outliers in time series seriously affect conventional parameter estimates. In this paper a robust recursive estimation procedure for the parameters of auto-regressve moving-average models with additive outliers is proposed. Using 'cleaned' residuals from an initial robust fit of an autoregression of high order as input, bounded influence regression is applied recursively. The proposal follows certain ideas of Hannan and Rissanen, who suggested a three-stage procedure for order and parameter estimation in a conventional setting.
A Monte Carlo study is performed to investigate the robustness properties of the proposed class of estimates and to compare them with various other suggestions, including least squares, M estimates, residual autocovariance and truncated residual autocovariance estimates. The results show that the recursive generalized M estimates compare favourably with them. Finally, possible modifications to master even vigourous situations are suggested.     

Application of a rice field experimental error distribution function to nitrogen-phosphorus-potassium fertilizer response model analysis

A distribution function of rice yield deviations from the mean was developed from field experiments with 555 plots at 16 sites in Zhejiang province, China, for three years. The deviation distribution in interval of 50kg/ha appeared as a symmetrical distribution with a high peak (Mean=0.279 [kg/ha], SD=240.686 [kg/ha]). Normality test using Kolmogrove-Smirnov test between the observed cumulative distribution and the normal cumulative distribution function indicates that the observed deviation distribution is not normal. An empirical exponential cumulative distribution function was developed. The distribution function was used to remove outliers during the development of a rice yield fertilizer response model, based on data from a non-replicated NPK field experiment.     

臭氧氧化法除地表水有机物试验研究

本文阐述臭氧化法除地表水有机物的重要意义，实验结果表明：臭氧氧化有机物的总氧化速率受活化控制，影响氧化率的最高显著因素是温度，其次是ｐＨ，接触时间等，臭氧很容易氧化腐植酸，在３０℃，ｐＨ９．０～１０．０，７ｍｉｎ内，ＣＯＤ去除率可达６０％以上，对邯郸热电厂生产处理也取得良好效果，３５℃，ｐＨ７．４～７．６，１０ｍｉｎ内，ＣＯＤ去除率可达６７％，可望将臭氧化水处理工艺应用于电厂水处理。     

一种基于自然最近邻的离群检测算法

任何涉及k近邻求解问题的算法被应用于处理不同特征的数据集时,参数k值的选择都会明显影响算法的性能和结果。因而,如何选择k近邻算法中敏感参数k值一直是一个研究难点。提出了一种新的近邻关系———自然最近邻,它不需要设置参数k,每个节点的邻居是由算法自适应计算而形成的。针对离群点检测的特殊性,通过确定自然最近邻居搜索算法的终止条件,提出一种基于自然最近邻的新的离群检测算法ODb3N。实验表明,该算法不仅避免了k近邻中参数的选择问题,而且能够更有效地发现离群簇。     

基于云计算的去小型机研究

基于对R1SC和x86CPU的分析,结合大量的研究数据,研究了去小型机的必要性和可能性。通过分析可以清晰认识到,x86服务器已经从性能、可靠性、可用性、服务能力等方面全面满足云计算的需求。     

PEAK-INSENSITIVE NON-PARAMETRIC SPECTRUM ESTIMATION

Abstract. We study the problem of non-parametric spectrum estimation of a stationary time series that might contain periodic components. In this case the periodogram ordinates have a significant amplitude at frequencies near the frequencies of the periodic components. These can be regarded as outliers in an asymptotically exponential sample. We develop a non-parametric estimator for the spectral density that is insensitive to these outliers in the frequency domain. This is done by robustifying the usual kernel estimator (smoothed periodogram) by means of M-estimation in the frequency domain. We propose to use data-tapered periodograms, which yield a drastic improvement of the procedure, typically for the contaminated situation. This is both shown theoretically and supported by means of simulation. We show consistency of the resulting estimator in the general case, and asymptotic normality in the special case of a Gaussian time series, whether contamination is present or not. Finally we illustrate the finite sample performance of the estimating procedure by some simulation results and by application to the Canadian lynx trappings data.     

Range Unit‐Root (RUR) Tests: Robust against Nonlinearities,Error Distributions,Structural Breaks and Outliers

Abstract. Since the seminal paper by Dickey and Fuller in 1979, unit‐root tests have conditioned the standard approaches to analysing time series with strong serial dependence in mean behaviour, the focus being placed on the detection of eventual unit roots in an autoregressive model fitted to the series. In this paper, we propose a completely different method to test for the type of long‐wave patterns observed not only in unit‐root time series but also in series following more complex data‐generating mechanisms. To this end, our testing device analyses the unit‐root persistence exhibited by the data while imposing very few constraints on the generating mechanism. We call our device the range unit‐root (RUR) test since it is constructed from the running ranges of the series from which we derive its limit distribution. These nonparametric statistics endow the test with a number of desirable properties, the invariance to monotonic transformations of the series and the robustness to the presence of important parameter shifts. Moreover, the RUR test outperforms the power of standard unit‐root tests on near‐unit‐root stationary time series; it is invariant with respect to the innovations distribution and asymptotically immune to noise. An extension of the RUR test, called the forward–backward range unit‐root (FB‐RUR) improves the check in the presence of additive outliers. Finally, we illustrate the performances of both range tests and their discrepancies with the Dickey–Fuller unit‐root test on exchange rate series.