非线性凸半定规划的割平面算法

先把一般的非线性凸半定规划转化成目标函数是线性函数的非线性凸半定规划,然后用割平面算法求解转化后的半定规划．最后证明了割平面算法的收敛性．     

算法及其教育价值

2003年颁布的《高中数学课程标准(实验)》,其中“算法”是一个全新的内容.算法内容的教育价值主要体现在:(1)算法内容有利于培养学生的思维能力;(2)算法内容有利于培养学生理性精神和实践能力;(3)算法内容有利于学生理解构造性数学;(4)算法内容反映了时代的特点,同时也是中国数学课程内容的新特色.     

An efficient enhanced k-means clustering algorithm

INTRODUCTION The huge amount of data collected and stored in databases increases the need for effective analysis methods to use the information contained implicitly there. One of the primary data analysis tasks is cluster analysis, intended to help a user understand the natural grouping or structure in a dataset. Therefore, the development of improved clustering algorithms has received much attention. The goal of a clustering algorithm is to group the objects of a database into a set of m…     

题库管理系统的研究与实现

阐述了试题命题的基本要求,并提出基于题型、难度与章节的合理三维立体关系的组卷算法.在此基础上,设计题库管理系统的后台数据库,同时对题库管理系统的题库建立、试题组卷、试卷生成、试卷分析以及系统维护等功能模块实现等做了阐述.     

融合Apriori优化算法与Relim算法的抑郁症用药规律挖掘

为明确中医治疗抑郁症用药规律,融合Apriori优化算法与Relim算法,采用数据挖掘技术进行分析。针对传统Apriori算法频繁扫描数据库从而生成大量候选项集的缺点,改变其原有剪枝方式以减少扫描次数。将改进后的Apriori算法与无需产生候选项集的Relim算法就中医治疗抑郁症的方剂数据进行关联规则分析,并绘制两个算法时间效率图。结果发现,两种算法在挖掘药物频繁项集与关联规则的结果基本相同,通过分析发现,中医常以疏肝、理气、补肾、滋阴等药物为主治疗抑郁症。改进后的Apriori算法可降低数据库扫描次数,较传统Apriori算法运行效率有所提高,Relim算法在空间利用率和时间执行率上均略优于改进后的Apriori算法。两种算法挖掘结果体现出中医治疗抑郁症注重疏肝理气、补肾滋阴、调理气血等特点。基于关联规则的方法可作为中医用药规律分析的重要工具。     

基于HJPS算法的神经网络的轧制力修正模型

传统的轧制力模型结构简单、精度较低,即使采用基于有限元的数值积分方式进行精化,出于计算效率的考虑因其有限区域的划分十分有限,因此对于轧制力计算的精度提高有限。直接采用神经网络对轧制力进行建模可以极大地提高模型精度,但是模型对新型材料的泛化能力较差。为此提出简单有限元轧制力模型,并在模型基础上使用HJPS优化算法的神经网络对轧制力进行修正,对该模型的仿真测试表明,该模型具有很强的泛化能力,收敛速度快、不易陷于局部优化,能够极大地提高轧制力模型的计算精度。     

决策树算法研究综述

分类在数据挖掘中是一项非常重要的任务,决策树方法是一种常用的方法。本文重点介绍了决策树建立的基本原理,对算法所面临的问题进行了阐述,为数据分类研究者提供借鉴．     

网络化控制系统的转换控制算法

对于延迟大于一个采样周期的网络化控制系统,本文提出了一种转换控制算法,根据延迟落入的不同概率区间选取对应的控制器,进行转换控制,仿真结果验证了算法的有效性。     

On modal energy in civil structural control

A new control strategy based on modal energy criterion is proposed to demonstrate the effectiveness of the control system in reducing structural earthquake responses. The modal control algorithm combining LQR （linear quadratic regulator） control algorithm is adopted in the discrete time-history analysis. The various modal energy forms are derived by definition of the generalized absolute displacement vector. A preliminary numerical study of the effectiveness of this control strategy is carried out on a 20-storey framed steel structural model. The controlled performance of the model is studied from the perspectives of both response and modal energy. Results show that the modal energy-based control strategy is very effective in reducing structural responses as well as in consuming a large amount of modal energy, while augmentation of additional generalized control force corresponding to the modes that contain little modal energy is unnecessary, as it does little help to improve the controlled structural performance.     

Two-stage evolutionary algorithm for dynamic multicast routing in mesh network

In order to share multimedia transmissions in mesh networks and optimize the utilization of network resources, this paper presents a Two-stage Evolutionary Algorithm （TEA）, i.e., unicast routing evolution and multicast path composition, for dynamic multicast routing. The TEA uses a novel link-duplicate-degree encoding, which can encode a multicast path in the link-duplicate-degree and decode the path as a link vector easily. A dynamic algorithm for adding nodes to or removing nodes from a multicast group and a repairing algorithm are also covered in this paper. As the TEA is based on global evaluation, the quality of the multicast path remains stabilized without degradation when multicast members change over time. Therefore, it is not necessary to rearrange the multicast path during the life cycle of the multicast sessions. Simulation results show that the TEA is efficient and convergent.