搜索资源列表
hPSO
- 多目标遗传算法求解多目标优化问题的实际例子，运用matlab编写-Multi-objective Genetic Algorithm for multi-objective optimization problem actual examples, the use of Matlab prepared
imm.rar
- 本程序是matlab编写的imm（交互式多模型算法）目标跟踪程序。这种方法的特点是在各模型之间“转换”，自动调节滤波带宽，和适合机动目标的跟踪。,This program is matlab written imm (interacting multiple model algorithm) target tracking program. This method is characterized among the various models " conversion" ,
12345
- 分析量子进化算法和免疫算子的特点,提出一种分级变异的量子进化算法,用于求解多目标优化问题-Analysis of quantum-inspired evolutionary algorithms and immune operator characteristics, presents a hierarchical variation of the quantum-inspired evolutionary algorithm for solving multi-objective optimi
mopsocd
- 这是一个基于距离的多目标粒子群优化算法C语言实现-This is an implementation of MOPSO-CD,a multiobjective particle swarm optimization algorithm using crowding distance
MP_DOA
- 针对多径效应的影响，提出了一种基于矩阵束的MIMO 雷达低仰角快速估计方法。该方法同时考虑了发射多径信号和接收多径信号，采用单样本数信号矢量构造了一个前后向矩阵束，并利用两个酉矩阵对该矩阵束进行降维处理，最后采用广义特征值分解的总体最小二乘法来估计目标角度。算法不需要估计数据协方差矩阵，可在低 信噪比和单样本数情况下，有效地克服多径效应，实现同时多目标低仰角估计，相比最大似然算法，避免了谱峰搜索，计算量小。仿真结果验证了该算法的有效性。-To overcome the multipath e
mubiaoguihua
- 采用序贯式算法解决多目标规划问题，虽然不能得到严格的最优解，但能够得到满意解。-Sequential algorithm to solve multi-objective programming problem, although it can not be strictly optimal solution, but able to get a satisfactory solution.
mpso
- 多目标粒子群优化算法，利用粒子群算法原理编写优化两个目标函数。-Multi-objective particle swarm optimization algorithms, particle swarm optimization principle to write to optimize the two objective functions.
MOPSOwang
- 关于模糊车辆路径问题的多目标粒子群算法，里面有作者提出的实数编码方式，在经典的MOPSO基础上完成的。模糊包括模糊需求、模糊旅行时间和模糊服务时间多重模糊特性。-Fuzzy vehicle routing problem with multi-objective particle swarm algorithm, which has the real number encoding, proposed by the authors in classic MOPSO based on. Fuzzy
LVQ
- 实现LVQ（Learning Vector Quantization）算法的VB源码，适合多目标对象的函数模型建立，附测试数据和调用方法实例。按不同使用需求，需要用户适当优化调整，此方法对具备或理解LVQ原理+vb编程的用户最佳。如果你觉得好，谢谢支持！ -LVQ (Learning Vector Quantization) algorithm VB source, multi-target object function modeling, attached test data and c
WTClass
- 实现逐步判别方法的vb源码，可以对已知的多目标对象进行函数建模识别，输出计算过程中间数据以便查验；输出选出的因子和判别系数；输出判别方程及合率；如果有检验集，可输出判别方程的推广能力。侧重算法实现，一般界面，易用性好，如果觉得好，多谢支持！-Vb source stepwise discriminant function modeling to identify multi-target object known, the output calculated the middle of the
multi
- 带等式约束的多目标遗传算法工具箱nondominated sorting genetic algorithmⅡ，NSGA-Ⅱ优化源代码-With equality constraint multi-objective genetic algorithm toolbox nondominated sorting genetic algorithm Ⅱ NSGA-II optimized source code
matlab-code
- 几个多目标求极值的Matlab算法，包括模式搜索法、Rosenbrock法、单纯形法、Powell法、最速下降法、共轭梯度法、牛顿法、信赖域法-Matlab algorithm, several multi-objective extremum including pattern search method, Rosenbrock method, simplex method, Powell method, the steepest descent method, conjugate gradi
samplesfsaf
- PSO算法进行多目标寻优，主要包括主程序和算例说明。-PSO algorithm for multi-objective optimization, includes the main program and a numerical example.
Multi-Target
- 多目标的数据关联融合处理算法，应用于决策级的目标类型判断等处理。-Multi-target data association fusion algorithm, applied to determine the type of decision-making level goals such treatment.
NSGA2
- 用Matlab实现的NSGA2多目标优化算法的源程序，用户可以根据需要定义相应的参数-Using Matlab multi-objective evolutionary algorithm to achieve the source, the user can define the parameters of the corresponding
jMetalPy-master-python
- 用Python语言写的多目标进化算法库（2017年最新版本），包含常见的多目标进化算法以及当前最新文献中的最新算法，能够实现不同算法之间的性能比较（包含常见的GD, IGD, HV等评价指标自动生成）。可以供进化计算、多目标优化、单目标优化算法的学习参考。Python语言版本简单易懂，实用性强。(Library of multi-objective evolutionary algorithm written in Python language (the latest version in 2
多目标蚁群算法
- 多目标蚁群算法用来求解多目标最小生成树问题(Multi-objective ant colony algorithm)
moead-java-source
- java文件的多目标优化算法，代码函数已经封装，可以在java平台跑通(Java file multi-objective optimization algorithm, the code function has been encapsulated, can run on the Java platform)
基于多目标的创意平板卓设计
- 平板折叠桌结构简单，造型美观，通过桌腿的翻转形成美丽的直纹曲面。本算法旨在通过稳固性，加工方便，用料最少三个方面建立数学模型，得出平板桌设计的最优方案。(The plate folding table has simple structure and beautiful shape, and forms beautiful straight surface through the flip of the table leg. This algorithm aims at stability, e
NSGA-II
- matlab实现的多目标优化遗传算法代码。可输出结果并画图。(The matlab program of NSGA-II.)