PC Accelerator让PC“飞”起来

PC Accderator应该算是一个老牌的PC性能优化软件了，它有着卓越的优化性能与高度的整合性。可为我们合理调配网络、系统、显卡等软硬件的参数设置，从而有效地提高网络速度、显示性能以及系统整体性能。那么，我们究竟应该如何利用Pc Accelerator来优化并提高PC性能呢?并且，通过PC Accelerator的优化，究竟能够从多大程度上提高PC件能呢？     

嵌入式Java虚拟机的性能优化技术

分析了线索化和直接线索化等基于解释运行的性能优化技术，实现了基于直接线索化技术的嵌入式Java虚拟机的解释器性能优化方案，并对嵌入式Java虚拟机的参考实现、线索化优化方案和基于直接线索化的优化方案进行了性能对比。     

基于B/S模式应用系统性能优化的研究

如何提高B／S模式应用系统的性能，一直是困扰应用系统设计和开发人员的主要问题之一，通过对B／S系统结构特征，TCP／IP和HTTP传输协议对系统性能影响的分析，找出了影响B／S模式应用系统性能的主要因素，为系统性能优化提供了理论依据和一般的优化策略，并讲述了一些用于B／S系统性能优化的有效方法。     

分布事务管理器的性能优化

作为应用服务器重要组成部分的分布管理器主要用于提供分布环境下的事务处理能力，它的性能是制约应用服务器上分布事务吞吐能力的重要因素。讨论了在J2EE应用服务器框架下如何进行分布事务管理器的性能优化，同时给出了分布事务管理器ISTX的性能优化实现。实验数据表明，对ISTX的性能优化能在保证分布事务可靠性的前提下，较大幅度地提高了分布事务处理的性能。     

提高Access数据库性能的几种方法

对于一个完整的数据库系统，性能的优化是很重要的。你可以根据计算机的配置和工作环境，做一些事来提高数据库的性能。Access提供了多种优化数据库的方法，下面向你介绍常用的几种。方法一：用“性能分析器”优化数据库的性能最好的优化方法就是使用“性能分析器”，使用它可以分析整个数据库或只分析数据库中所选择的对象，它将针对你的需要做一些建议性的更改。在设计数据库时，可以利用它来优化数据库的性能，从而改进自己的设计工作。具体方法为：1．打开要优化的数据库；2．在“工具”菜单上，指到“分析”，然后单击“性能”命令；3…     

SQL Server数据库性能优化

提出了影响SQL Server数据库性能的一些因素及SQL Server进行性能优化的原理，并给出了一些指导性的原则来优化数据库的性能。     

MIS数据库性能优化

针对MIS数据库中普遍存在的效率问题，对影响数据库性能的相关因素进行了分析，提出了性能优化的方法和途径。优化数据库是一个系统工程，若单纯注重某一方面的优化不能取得整体效果，应将效率意识贯穿于应用开发的全过程。     

基于ASP.NET缓存与分页策略优化Web数据查询性能

利用ASP．NET的缓存功能，结合性能良好的存储过程，一次性地缓存数据库数页数据，以供用户分页查询，是优化Web数据查询性能的比较理想的方式。文章详细介绍了优化模型的实现，并进行了性能分析。     

TSP问题次优化求解方法的比较

针对几种次优化求解了ＴＳＰ的方法，通过计算机仿真对优化性能，时间性能，波动性进行了比较研究，并归纳出各方法的特点和适用域。对大规模网络优化问题提出了分区分层化的思路，并通过仿真说明其可行性。     

你信不信？60%硬盘性能的提升

使用某某软件优化而提高硬盘性能也不是什么新鲜的事情了，这些软件都是硬盘厂商针对自家产品而推出的优化程序。虽说提高性能，但根据过往的经验，对硬盘性能近日，著名的硬盘制造商迈拓(Maxtor)发布了一款名为MaxBoost的磁盘驱动，按照平常的惯例，这是一款对硬盘起到优化作用的程序而     

基于近似模型的y轴微机械陀螺系统级优化

提出一种基于近似模型的MEMS系统级优化方法,给出具体实现流程,并结合一个y轴微机械陀螺进行优化。该方法解决了如何得到近似优化目标函数表达式的关键问题。所得的y轴微机械陀螺优化参数,使得陀螺驱动模态谐振频率fx和检测模态谐振频率fz分别为3 074 Hz和2 998 Hz,两者之间相差7 6 Hz,较好的实现了模态匹配,且都在3 000 Hz的设计要求附近,约束条件也得到了满足。该优化方法为在MEMS设计中快速获得系统级优化方案提供较好参考。     

广域网优化技术及其应用

通过对广域网优化技术的应用背景和几种主要的广域网链路优化技术的分析,结合广域网优化技术的实际部署案例,探讨广域网优化技术在广域网络和应用系统性能优化中的应用.     

pyOpt: a Python-based object-oriented framework for nonlinear constrained optimization

We present pyOpt, an object-oriented framework for formulating and solving nonlinear constrained optimization problems in an efficient, reusable and portable manner. The framework uses object-oriented concepts, such as class inheritance and operator overloading, to maintain a distinct separation between the problem formulation and the optimization approach used to solve the problem. This creates a common interface in a flexible environment where both practitioners and developers alike can solve their optimization problems or develop and benchmark their own optimization algorithms. The framework is developed in the Python programming language, which allows for easy integration of optimization software programmed in Fortran, C, C+ +, and other languages. A variety of optimization algorithms are integrated in pyOpt and are accessible through the common interface. We solve a number of problems of increasing complexity to demonstrate how a given problem is formulated using this framework, and how the framework can be used to benchmark the various optimization algorithms.     

Objective fuzzy subsets and an algorithm for partial linear programming

People do know how to use optimization to search the peak points of fuzzy subsets. This paper presents an inverse approach: how to treat optimization as peak-searching of fuzzy subsets. The author presents the concepts of objective fuzzy subsets and apt objective fuzzy subsets. This work shows how to use objective fuzzy subsets to treat the optimization problem. Based on the apt objective fuzzy subsets, the author formulates and resolves a new kind of optimal program problem, Partial Linear Programming problem. This work supported by a Research Enhancement Grant, West Texas A&M University, 2001.     

Importance Driven Texture Coordinate Optimization

Traditionally, texture coordinates have been generated based solely on the model's geometry, often even before a model's textures have been created. With the arrival of new technologies, such as 3D paint programs, weaknesses of a static optimization pre-process are becoming apparent. These weaknesses arise from constructing a parameterization based solely on the model's geometry, ignoring the fact that detail is not uniformly spaced throughout the texture space. In fact, certain regions of the texture are more important than other regions. In this paper we introduce the notion of the "importance map" and describe how importance values are derived from both intrinsic properties of the texture and user-guided highlights. Furthermore, we describe how importance maps are used to drive the texture coordinate optimization. Finally, we show how this optimization process can be integrated into a 3D painting environment, enabling periodic optimization at any stage of texture design.     

A feedback scheduler for real-time controller tasks

The problem studied in this paper is how to distribute computing resources over a set of real-time control loops in order to optimize the total control performance. Two subproblems are investigated: how the control performance depends on the sampling interval, and how a recursive resource allocation optimization routine can be designed. Linear quadratic cost functions are used as performance indicators. Expressions for calculating their dependence on the sampling interval are given. An optimization routine, called a feedback scheduler, that uses these expressions is designed.     

Oracle性能调整技术研究

该文以ORACLE数据库性能优化的基本原则为出发点,主要研究在数据库设计阶段如何避免竞争和如何优化数据访问,在数据库运行阶段如何从操作系统和数据库实例级别上调整内存和I/O来达到数据库性能优化的各种技术。     

Improving the Solution of Variational Inequalities Based on the Optimization Approach

An optimization approach to solving a convex finite-dimensional variational inequality with nonpotential operator is examined. It is shown how to construct an optimization problem equivalent to the variational inequality in the space of the original variables. A first-order algorithm to solve variational inequalitieis is formulated based on this optimization problem.     

Adaptive comprehensive learning particle swarm optimization with spatial weighting for global optimization

Multimedia Tools and Applications - Although particle swarm optimization (PSO) algorithm shows excellent performance in solving optimization problems, how to balance exploration and exploitation is...     

离散粒子群优化算法求解旅行商问题

在优化领域,粒子群算法适用于求解连续优化问题,而在离散优化上的应用还相对较少。本文在介绍基本粒子群优化算法的基础上,分析了粒子群优化算法在经典旅行商问题 中的应用性能及粒子群算法求解旅行商问题的相关操作。使用Ulysses等标准TSP测试数据进行了相关实验,并通过不同的参数设置对实验结果进行了性能分析和比较。