粒子物理中几种可能应用的新数学方法和拓扑模型

在粒子物理中探讨了四元数、符号动力学等新的数学方法,几种可能应用于振荡的数学方法,及与时间有关的粒子理论;讨论了非线性理论和相应的定性分析理论的结果;研究了粒子的拓扑模型和分形模型;最后提出弱相互作用可能相应于Lobachevsky几何.     

约束优化问题稳定序列二次规划方法研究综述

稳定序列二次规划(sSQP)方法由于在求解病态或退化约束优化问题获得理论与数值的突破性进展而备受关注,重要成果频繁问世.本文对近期国际上若干重要sSQP方法及其思想进行概述,包括罚函数型sSQP方法,滤子型sSQP方法和非精确恢复(IR)型sSQP方法等,并对约束优化问题sSQP方法的进一步研究进行探索性思考.     

An Adaptive Multiscale Ensemble Learning Paradigm for Nonstationary and Nonlinear Energy Price Time Series Forecasting

For forecasting nonstationary and nonlinear energy prices time series, a novel adaptive multiscale ensemble learning paradigm incorporating ensemble empirical mode decomposition (EEMD), particle swarm optimization (PSO) and least square support vector machines (LSSVM) with kernel function prototype is developed. Firstly, the extrema symmetry expansion EEMD, which can effectively restrain the mode mixing and end effects, is used to decompose the energy price into simple modes. Secondly, by using the fine‐to‐coarse reconstruction algorithm, the high‐frequency, low‐frequency and trend components are identified. Furthermore, autoregressive integrated moving average is applicable to predicting the high‐frequency components. LSSVM is suitable for forecasting the low‐frequency and trend components. At the same time, a universal kernel function prototype is introduced for making up the drawbacks of single kernel function, which can adaptively select the optimal kernel function type and model parameters according to the specific data using the PSO algorithm. Finally, the prediction results of all the components are aggregated into the forecasting values of energy price time series. The empirical results show that, compared with the popular prediction methods, the proposed method can significantly improve the prediction accuracy of energy prices, with high accuracy both in the level and directional predictions. Copyright © 2016 John Wiley & Sons, Ltd.     

LEARNING CAUSAL GRAPHS OF NONLINEAR STRUCTURAL VECTOR AUTOREGRESSIVE MODEL USING INFORMATION THEORY CRITERIA

Detection and clarification of cause-effect relationships among variables is an important problem in time series analysis. Traditional causality inference methods have a salient limitation that the model must be linear and with Gaussian noise. Although additive model regression can effectively infer the nonlinear causal relationships of additive nonlinear time series, it suffers from the limitation that contemporaneous causal relationships of variables must be linear and not always valid to test conditional independence relations. This paper provides a nonparametric method that employs both mutual information and conditional mutual information to identify causal structure of a class of nonlinear time series models, which extends the additive nonlinear times series to nonlinear structural vector autoregressive models. An algorithm is developed to learn the contemporaneous and the lagged causal relationships of variables. Simulations demonstrate the effectiveness of the nroosed method.     

C语言教学中的常见问题和解决方案

本文从实际工作出发,阐明了在C语言教学活动中存在的主要问题,并从教师、学生两方面入手,对问题的成因进行了详细的分析,最后结合教学经验,提出解决方案,为提升学生学习效果,提升我校C语言教学质量做出有益探讨。     

Some Open Problems in Parameterized Complexity Related to the Work of Jianer Chen

This short paper highlights some open problems related to the work of Jianer Chen in the area of parameterized/multivariate algorithmics.     

基于PSO优化LS-SVM的小样本非线性协整检验与建模研究

针对小样本非线性时间序列，根据非线性协整的定义，利用基于粒子群优化最小二乘支持向量机的方法，对小样本非线性协整关系检验与非线性误差修正模型建模进行研究，设计了方法的 逻辑流程. 对舰船维修费指数与物价指数进行实证研究，在协整关系类型判断的基础上，实现了小样本非线性协整关系的检验，建立了预测舰船维修费指数的非线性误差修正模型，并与线 性向量自回归模型进行分析比较. 研究表明：基于粒子群优化最小二乘支持向量机的小样本非线性协整检验与建模方法，刻画了小样本系统的非线性协整关系，所建立的非线性误差修正模 型具有较好的预测效果，能够有效地预测小样本非线性系统.     

求解非线性互补问题的混合光滑型算法

光滑型算法已经成功地用来求解各种优化问题. 基于一类新的光滑函数族， 提出了一个带有混合线搜 索的光滑型算法求解非线性互补问题. 在适当的条件下， 证明了算法是适定的， 且保持全局 收敛性和局部超线性收敛性. 最后对提出的算法进行了数值计算. 数值结果显示出该算法的有效性.     

基于MVDR波束形成的FDA平台外干扰抑制

针对频控阵(frequency diverse array, FDA)在对与目标位置相近的平台外干扰进行抑制时, 传统FDA与非线性频偏结合不能实现距离-角度去耦合、对数递增FDA主瓣展宽较大和汉明窗加权FDA距离维旁瓣过高的问题, 在充分研究汉明窗加权的线性FDA(Hamming linear FDA, HL-FDA)方案的基础上, 对4种频偏方案的性能进行了分析, 提出采用FDA多输入多输出结构代替传统的一维均匀线性FDA结构, 通过结合最小方差无失真响应(minimum variance distortion free respinse, MVDR)准则, 将HL-FDA应用到MVDR自适应波束形成层面, 对平台外干扰进行抑制。仿真验证了HL-FDA在结合MVDR自适应波束形成算法后能有效地对抗距离-角度二维平台外干扰。     

信息物理融合系统中恶意软件传播与分岔控制策略

针对恶意软件在信息物理融合系统中传播机理难以描述的问题,利用非线性动力学理论构建其传播动力学模型,并基于稳定性理论和Hopf分岔定理对该模型的复杂动力学行为进行分析.为了控制恶意软件传播所引发的Hopf分岔,根据分岔控制理论设计了一类结合参数调节法与状态反馈法的混合分岔控制策略,并深入研究控制参数对Hopf分岔点位置及极限环幅值的影响.数值仿真结果表明所设计的混合分岔控制策略不仅能够提前或推迟Hopf分岔点,而且可以改变极限环幅值大小,使信息物理融合系统产生预期的动力学行为,实现控制目的,从而有效降低恶意软件的危害.