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.     

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。     

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.     

Bounds to optimal burn‐in and optimal work size

Burn‐in is a widely used method to improve the quality of products or systems after they have been produced. In this paper, we consider the problem of determining the optimal burn‐in time and optimal work size maximizing the long‐run average amount of work saved per time unit in the computer applications. Assuming that the underlying lifetime distribution of the computer has an initially decreasing or/and eventually increasing failure rate function, an upper bound for the optimal burn‐in time is derived for each fixed work size and a uniform (with respect to the burn‐in time) upper bound for the optimal work size is also obtained. Furthermore, it is shown that a non‐trivial lower bound for the optimal burn‐in time can be derived if the underlying lifetime distribution has a large initial failure rate. Copyright © 2005 John Wiley & Sons, Ltd.     

Predictability and model selection in the context of ARCH models

Most of the methods used in the ARCH literature for selecting the appropriate model are based on evaluating the ability of the models to describe the data. An alternative model selection approach is examined based on the evaluation of the predictability of the models in terms of standardized prediction errors. Copyright © 2005 John Wiley & Sons, Ltd.     

两相同部件温贮备可修的人机系统解的性质分析

本文首先用强连续算子半群理论证明了两相同部件温贮备可修的人机系统动态非负解的存在唯一性 ,然后证明了 0是系统主算子的本征值 ,并得到 0本征值对应的本征向量是正的 ,从而系统存在稳态正解 .     

Non-Parametric Regression Methods

The nature of the financial time series is complex, continuous interchange of stochastic and deterministic regimes. Therefore, it is difficult to forecast with parametric techniques. Instead of parametric models, we propose three techniques and compare with each other. Neural networks and support vector regression (SVR) are two universally approximators. They are data-driven non parametric models. ARCH/GARCH models are also investigated. Our assumption is that the future value of Istanbul Stock Exchange 100 index daily return depends on the financial indicators although there is no known parametric model to explain this relationship. This relationship comes from the technical analysis. Comparison shows that the multi layer perceptron networks overperform the SVR and time series model (GARCH).     

对优秀跳远运动员助跑准确性的研究

通过对全国第十届运动会37名男女跳远运动员比赛的调查和分析,研究表明：第一，运动员的前三轮试跳助跑准确性、稳定性较好，而在后三轮试跳助跑准确性、稳定性较差，极大地影响了他们正常水平的发挥．第二，心理因素对跳远助跑的准确性有较大的影响,建议在今后的训练中加强在特殊状态下助跑技术稳定性的训练．     

斜坡变形破坏的预测及防护

通过对斜坡变形破坏和影响因素的研究，探讨工程建设中斜坡变形破坏的预测及防护。