利用反预报方法从截面预言近滴线丰质子核的结合能

在Origin等数据处理软件中,当实验数据较少时,自由参数的不同初始化设置会导致较大的结果差异,这为物理结果的确定带来较大不确定性.通过最小二乘法分析了345MeV/u ~(78) Kr+~9Be反应中产生的丰质子同位素的截面和结合能,并得到线性回归方程.通过回归方程,利用结合能预报部分丰质子核素的截面,以及通过实验截面对近质子滴线核素的结合能进行反预报测量.这对于近质子滴线的丰质子核素实验测量具有较好的借鉴意义.     

大尺寸工程模型试验中的相似材料配比试验研究

大型物理模型试验是研究复杂工程问题的重要方法，如何快速、准确地确定相似材料配比是试验中至关重要的一环.为降低试验成本、简化试验步骤、充分调用原料性能，采用河砂、水泥和石膏这三种最普通的原料，以骨胶比(河砂与水泥石膏的质量比)和水膏比(水泥与石膏的质量比)为变量，进行了45组对比试验，对相似材料的物理及动、静力学参数进行了研究.获得了以河砂、水泥和石膏为原料配制的相似材料各物理量的变化区间；探讨了骨胶比和水膏比对相似材料各物理量的控制作用，并对比了其敏感性；基于多元线性回归分析建立了各因素与物理量间的定量关系，得到的拟合公式能较好地描述相似材料的性质.     

线性回归分析与能源需求预测

结合实例介绍了回归模型方法在能源预测中的应用，具体地讨论了最简单、最基本的直线回归模型结构及参数估计方法，对于其他一些曲线回归模型则可通过变量代换转化为直线回归模型。     

Robustness of alternative non‐linearity tests for SETAR models

In recent years there has been a growing interest in exploiting potential forecast gains from the non‐linear structure of self‐exciting threshold autoregressive (SETAR) models. Statistical tests have been proposed in the literature to help analysts check for the presence of SETAR‐type non‐linearities in an observed time series. It is important to study the power and robustness properties of these tests since erroneous test results might lead to misspecified prediction problems. In this paper we investigate the robustness properties of several commonly used non‐linearity tests. Both the robustness with respect to outlying observations and the robustness with respect to model specification are considered. The power comparison of these testing procedures is carried out using Monte Carlo simulation. The results indicate that all of the existing tests are not robust to outliers and model misspecification. Finally, an empirical application applies the statistical tests to stock market returns of the four little dragons (Hong Kong, South Korea, Singapore and Taiwan) in East Asia. The non‐linearity tests fail to provide consistent conclusions most of the time. The results in this article stress the need for a more robust test for SETAR‐type non‐linearity in time series analysis and forecasting. Copyright © 2004 John Wiley & Sons, Ltd.     

动态校正的PI型广义预测控制器及其在反应釜系统中的仿真研究

提出了一种新型的广义预测控制器。由于在控制器的设计中,进行了预测误差的动态校正,并且控制器采用了比例积分型(PI)目标函数,因此该控制器对未建模动态具有很强的鲁棒性。应用低阶的模型对一个强放热的化学反应釜模型进行的仿真研究检验了该方法的有效性。     

随机控制序在保险决策中的应用

通过介绍随机控制序的概念和性质 ,从而探讨了随机控制序在保险决策问题中的应用 ,得到了很有意义的结果     

证券投资组合理论和无差异曲线

文章通过无差异曲线解释了最优证券投资组合并探讨了对现代投资组合理论三个主要组成部分的有关内容.     

Finding finer functions for partially characterized proteins by protein-protein interaction networks

Based on high-throughput data, numerous algorithms have been designed to find functions of novel proteins. However, the effectiveness of such algorithms is currently limited by some fundamental factors, including (1) the low a-priori probability of novel proteins participating in a detailed function; (2) the huge false data present in high-throughput datasets; (3) the incomplete data coverage of functional classes; (4) the abundant but heterogeneous negative samples for training the algorithms; and (5) the lack of detailed functional knowledge for training algorithms. Here, for partially characterized proteins, we suggest an approach to finding their finer functions based on protein interaction sub-networks or gene expression patterns, defined in function-specific subspaces. The proposed approach can lessen the above-mentioned problems by properly defining the prediction range and functionally filtering the noisy data, and thus can efficiently find proteins’ novel functions. For thousands of yeast and human proteins partially characterized, it is able to reliably find their finer functions (e.g., the translational functions) with more than 90% precision. The predicted finer functions are highly valuable both for guiding the follow-up wet-lab validation and for providing the necessary data for training algorithms to learn other proteins.     

The controlling factors and distribution prediction of H2S formation in marine carbonate gas reservoir, China

Generally, there are some anhydrites in carbonate reservoir, as H2S is also familiar in carbonate oil and gas reservoirs. Nowadays, natural gas with high H2S concentration is usually considered as TSR origin, so there is close relationship between H2S and anhydrite. On the contrary, some carbonate rocks with anhydrite do not contain H2S. Recently, researches show that H2S is only a necessary condition of H2S formation. The reservoir porosity, sulfate ion content within formation water, reservoir temperature, oil/gas and water interface, hydrocarbon and some elements of reservoir rock have great controlling effects on the TSR occurrence. TSR deoxidizes hydrocarbon into the acidic gas such as H2S and CO2, and the H2S formation is controlled by TSR occurrence, so the relationship among reaction room, the contact chance of sulfate ion and hydrocarbon, the reservoir temperature has great influence on the TSR reaction. H2S has relatively active chemical quality, so it is still controlled by the content of heavy metal ion. Good conditions of TSR reaction and H2S preservation are the prerequisite of H2S distribu- tion prediction. This paper builds a predictive model based on the characteristic of natural gas reservoir with high H2S-bearing. In the porosity reservoir with anhydrite, the formation water is rich in sulfate and poor in heavy metal ion. Oil and gas fill and accumulate in the gas reservoir with good preservation conditions, and they suffered high temperature later, which indicates the profitable area of natural gas with high H2S-bearing.     

神经网络在可靠性分析中的应用

应用人工神经网络对舰炮发生故障的发射炮弹数进行了预测。借助前馈神经网络对非线性函数的逼近能力，对发生故障的发射炮弹数进行了单步预测，并与使用灰色数列预测的结果进行了对比，验证了人工神经网络进行可靠性预测的可行性。