搜索资源列表
PSO_immu
- 本程序为基于免疫的粒子群优化算法经典程序，本程序注释非常详细。是在免疫算法的基础上采用粒子群优化对抗体群体进行更新，解决了免疫算法收敛慢的缺点。-This procedure based on immune particle swarm optimization algorithm is a classic program. Is on the basis of immune algorithm USES the particle swarm optimization to update of
HMPSO
- A hybrid multi-swarm particle swarm optimization to solve constrained optimization
taobaospy1.3
- 程序带缓存，同步淘宝卖家更新！内页优化对百度。google有好！界面优化，给用户留下好影响。 -Program with cache, sync Taobao update! Inside pages optimization for Baidu. Google have good! Interface optimization, to leave a good impact on the user.
Matlab_code_Q-VMP
- Compressive sensing is the reconstruction of sparse images or signals very few samples, by means of solving a tractable optimization problem. In the context of MRI, this can allow reconstruction many fewer k-space samples, thereby reducing sc
GA-add-TO-BP
- matlab神经网络30例的案例3 遗传算法优化BP神经网络-非线性函数拟合-matlab neural network cases 30 cases of 3 genetic algorithm optimization BP neural network- a nonlinear function fitting
Optimization-in-Cognitive-Radio
- 该matlab程序源码主要实现单个认知用户频谱感知敏捷性的最优化，其基本的感知环节采用能量检测法；在恒漏检准则下，感知敏捷性可以用平均的感知时间来衡量；达到平均感知时间的最小化，也就实现了感知敏捷性的最优化。-The matlab main program source code to realize the optimization of single user spectrum sensing agility, its basic perceived links using energy d
Comparison-of-Optimization-Techniques-in-Large-Sc
- comparison of many different optimization techniques applied to a large scale transportation problem
optimization
- 利用梯度法，分别采用回溯直线搜索与一种精确直线搜索求解最优化问题-Using the gradient method, respectively, using backtracking linear search and a precise linear search to solve optimization problems
Improved-NSGA-II-Optimization
- 对NSGA-II算法进行改进，并应用于柔性车间调度的多目标优化问题-Of NSGA-II algorithm was improved and applied to flexible shop scheduling multi-objective optimization problem
yzipi
- 柚子皮wordpress主题免费下载,功能齐全优化到极致的小清新风格主题-Grapefruit skin wordpress theme download free, fully functional optimization to the limit of small fresh style theme
pso-optimization
- 粒子群优化算法PSO是可以用于各种神经网络的优化，然后可以进行分类。包含各种粒子群函数，matlab编写的。-PSO PSO is used to optimize a variety of neural networks, and can be classified. Particle swarm contains various functions, matlab prepared.
A-New-Unconstrained-Optimization-Method-based-on-
- In this paper, we try to use feedback control system as a new hybrid method to solve optimization problems. Because controller can control plant for a goal, if the plant is replaced by the cost function and the goal is changed to be solving o
Optimization-of-Back-Propagation-Network-Using-Si
- This research proposed a simulated annealing approach which not only provide the best architecture and parameter settings of BPN, but also find out the beneficial subset of features according to different problems, so that the results of BPN
Research-on-Optimization-of-Speed-Identification.
- Introducing the rank-weight method into the basic ant colony optimization (ACO), we use the modified ACO to optimize the weights and thresholds value of neural networks (NN). And when the BPNN is being trained, this method can solve the disad
To-predict
- matlab预测程序集合，适用于数学建模大赛，直接数据导入就可以用。包括灰色模型预测程序2个，gm10，greymodel，高斯混合模型mixture_of_gaussians，以及BP神经网络优化模型，遗传算法优化，Genetic，粒子群算法优化，PSO-Matlab to predict collection, suitable for mathematical modeling contest, data import can use directly. Including gray mo
zuiyouhua
- 基于modelcenter和粒子群算法MATLAB最优化解决装箱问题。包含代码、模块、PPT、课程论文-Based on MATLAB modelcenter and particle swarm optimization to solve the packing problem. It contains code modules, PPT, course papers
Particle_Swarm_Optimization
- 粒子群优化解决实际问题的方法，带有约束条件的，供大家参考学习-Particle Swarm Optimization to solve practical problems, with constraints, for your reference study
biogeography-based-optimization
- BBO Algorithm, biogepgraphy optimization algorithm used to solve any optimization problem
NSGAII optimization
- NSGA-II is a very famous multi-objective optimization algorithm. I submitted an example previously and wanted to make this submission useful to others by creating it as a function. Even though this function is very specific to benchmark problems, wit
2
- 基于交叉累计剩余熵的图像配准中插值方法的改进 交叉累计剩余熵（CCRE）比传统互信息在配准强噪声图像时更具优势,但采用部分体积（PV）插值的CCRE在网格点容易产生局部极值,不利于变换参数的优化。针对该问题,研究基于3阶B样条函数的PV插值（BPV）、哈宁窗sinc函数的PV插值（HPV）和Blackman-Harris窗sinc函数的PV插值（BHPV）方法在CCRE中的应用,提出一种新的插值方法。该方法采用灵活的邻域中心,将插值点对联合直方图贡献的权重分散到临近的9个点上,并使用高