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jmsla collection of mathematical, statistical and charting classes, written in 100 Java, marketed by Visual Numeric, Inc. Includes linear algebra, zero finding, splines, ordinary differential equations, linear programming, nonlinear optimization, FFT
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优化问题 线性、非线性 等 MATLAB程序 想看看的，可以看看优化问题的，-Optimization of linear, nonlinear, MATLAB program
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Particle swarm optimization has been used to solve many optimization problems since it was
proposed by Kennedy and Eberhart in 1995 [4]. After that, they published one book [9] and
several papers on this topic [5][7][13][15], one of which did a s
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有数值计算中常用的Visual Fortran子过程近200个，内容包括：解线性代数方程组、插值、数值积分、特殊函数、函数逼近、随机数、排序、特征值问题、数据拟合、方程求根和非线性方程组求解、函数的极值和最优化、傅里叶变换谱方法、数据的统计描述、解常微分方程组、两点边值问题的解法和解偏微分方程组，每一个子程序都包括功能、方法、使用说明、子程序和例子五部分。本书的所有子过程都在Visual Fortran 5.0版本上进行过验证，程序都能正确运行。同时配书发行光盘，包括所有子过程、验证过程及所有验
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介绍了一种基于最，j,-最大原理整定鲁棒PID控制器参数的方法，并应用MA ⅡAB
优化工具箱函数按非线性二次规划法搜索合理的PID参数。仿真结果表明，优化函数寻找
最佳PID参数简便可靠；当模型在一定范围内变化时，按该方法整定的鲁棒PID控制器均
能保证控制系统的动态性能良好。-Introduced based on the most, j,- setting the maximum principle method of robust PID controller paramet
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LINDO and LINGO software
LINGO and LINDO are computer software packages developed by LINDO systems.
designed for formulating and solving a wide variety of optimization problems include :
Linear programming
Integer programming
Nonlinear p
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求解0-1二次规划的粒子群算法
先将离散的0-1变量约束转化成了不光滑方程的约束，再用磨光函数方法对其光滑化。最终，把原来的数学模型转化为可微的非线性规划问题。最后，粒子群优化算法求解-0-1 first discrete particle swarm algorithm for solving 0-1 quadratic programming variable constraint transformed into smooth equations and constraints, it
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matlab中的非线性规划求解fmincon函数，能够实现参数传递条件的函数优化-The fmincon function,as the nonlinear optimization solver in matlab, can also realize optimization under the condition of parameter passing
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Cuckoo Optimization Algorithm, for solving nonlinear, complex & large scale engineering problems
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针对火电厂循环水加酸控制系统存在控制系统对象难以建立、非线性和时变的特性，采用了改进的粒子群优化
算法优化PID参数，使得控制器可在不同环境温度下采用不同的PID参数．实际运行结果表明，该系统能够克服环境温
度带来的干扰，使循环水pH值被控制在给定值范围内．-Water plus acid control system for thermal power plant control system exists object is difficult to establish, nonli
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基因算法的实现，采用随机方法计算非线性系统的优化-Genetic algorithm, using a random method of nonlinear systems optimization
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Abstract A particle swarm optimization method with nonlinear
time-varying evolution (PSO-NTVE) is employed in
designing an optimal PID controller for asymptotic stabilization
of a pendubot system. In the PSO-NTVE method,
parameters are determ
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Distributed Generators (DGs) in a microgrid may operate in three different reactive power control strategies, including PV, PQ and voltage droop schemes. This paper proposes a new stochastic programming approach for reactive power scheduling of a mic
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L-M(Levenberg—Marquardt)是一种非线性最优化里面最常用的方法之一，改方法能快速而准确的逼近收敛值。本文简述了改方法的操作原理和具体运用，如可以方便的用于有约束与无约束最优化的求解。-L- M (Levenberg- Marquardt) is a kind of nonlinear optimization inside one of the most commonly used method, change method can fast and accurate app
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提高电源的动态响应 非线性和复杂的系统是一个转换器 电力电子的有趣的挑战。摘要介绍了 设计和实现数字PID控制器使用 混沌粒子群优化(复)提振 转换器,提出了自动调优转换器的方法 最优启动响应。当系统启动时,处理器 单元分析了开环启动响应转炉和 在一些迭代使用复准备最佳反应 算法。使用逻辑映射混沌映射序列 增加它的收敛速度和精度。模拟 和实现结果显示提出的效率 方法-Improving dynamic response of DC-DC
converters whi
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We consider the source localization problem using
time-difference-of-arrival (TDOA) measurements in sensor networks.
The maximum likelihood (ML) estimation of the source
location can be cast as a nonlinear/nonconvex optimization
problem,
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Design of a Nonlinear PID Neural Trajectory Tracking
Controller for Mobile Robot based on
Optimization Algorithm
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In this paper, we study the issue of sensor network deployment using limited mobility sensors. By limited mobility, we mean
that the maximum distance that sensors are capable of moving to is limited. Given an initial deployment of limited mobility
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Matlab的fgoalattain解决悬置多目标解耦的非线性优化问题+实例-Nonlinear optimization problem of fgoalattain s Matlab to solve the problem of multi objective decoupling of suspension
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The genetic algorithm is a method for solving both constrained and unconstrained optimization problems that is based on natural selection, the process that drives biological evolution. The genetic algorithm repeatedly modifies a population of individ
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