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Description: In the last twenty years, the design of efficient function optimizers has been a crucial topic of research work. Many theoretical and practical research problems involve combinatorial optimization, which is obtaining the optimal solution among a finite set of alternatives. Such optimization problems are notoriously difficult to solve, one of the primary reasons being that in most applications the number of alternatives is extremely large and only a fraction of them can be considered within a reasonable amount of time (Shi et al, 1999). Indeed, such problems are often non-differentiable or multimodal, causing difficulties for classical gradient and random search methods, which are limited to simple unimodal functions and which are thus inappropriate to apply to such difficult problems. The seminal methods to deal with this problem are called Deterministic Optimization Methods (DOMs) (Fletcher, 1980). There are two major drawbacks when using DOMs: their high computational complexity and the possibility of becoming trapped in a local optimum. Moreover, DOMs are difficult to program, as they require a deep mathematical knowledge.
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Size: 12082 |
Author: dwenhcil@gmail.com |
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Description: simulation of unimodal image thresholding
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Size: 1190912 |
Author: sina |
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Description: Successive parabolic interpolation is a technique for finding the extremum (minimum or maximum) of a continuous unimodal function by successively fitting parabolas (polynomials of degree two) to the function at three unique points, and at each iteration replacing the "oldest" point with the extremum of the fitted parabola.
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Size: 1024 |
Author: Marcio |
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Description: CANOCO是一款针对生态学排序的需要而开发的。核心部分是基于线性模型的PCA和RDA,基于单峰模型的CA,DCA和CCA。-Canoco for Windows is the next generation of CANOCO software, the most popular tool for constrained and unconstrained ordination in ecological applications. Canoco for Windows integrates ordination with regression and permutation methodology, so as to allow sound statistical modelling of ecological data. Canoco for Windows contains both linear and unimodal methods.
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Size: 3253248 |
Author: liuruochen |
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Description: Among the high-complexity methods, two methods dominate the literature Kalman filtering and Mixture of Gaussians (MoG). Both have their advantages, but Kalman filtering gets slammed in every paper for leaving object trails that can t be eliminated. As this seems like a possible deal breaker for many applications, I went with MoG. Also, MoG is more robust, as it can handle multi-modal distributions. For instance, a leaf waving against a blue sky has two modes—leaf and sky. MoG can filter out both. Kalman filters effectively track a single Gaussian, and are therefore unimodal: they can filter out only leaf or sky, but usually not both. -Among the high-complexity methods, two methods dominate the literature Kalman filtering and Mixture of Gaussians (MoG). Both have their advantages, but Kalman filtering gets slammed in every paper for leaving object trails that can t be eliminated. As this seems like a possible deal breaker for many applications, I went with MoG. Also, MoG is more robust, as it can handle multi-modal distributions. For instance, a leaf waving against a blue sky has two modes—leaf and sky. MoG can filter out both. Kalman filters effectively track a single Gaussian, and are therefore unimodal: they can filter out only leaf or sky, but usually not both.
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Size: 80896 |
Author: mohammed fadhle |
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Description: The Nelder–Mead method or downhill simplex method or amoeba method is a commonly used nonlinear optimization technique, which is a well-defined numerical method for twice differentiable and unimodal problems. However, the Nelder–Mead technique is only a heuristic, since it can converge to non-stationary points on problems that can be solved by alternative methods.
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Size: 3072 |
Author: masha |
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Description: 为了提高部落只要看来fitnesse功能可以unimodal,我们需要一个明确的战略。这是一个(二分法)-In order to improve Tribes as long as it seems the fitnesse function may be unimodal, we need a specific strategy. Here is one (by dichotomy).
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Size: 3072 |
Author: 李晓 |
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Description: Omni-Optimizer (handles single and multiple objectives, unimodal or multi-modal problems)
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Size: 44032 |
Author: Hovering2008 |
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Description: Fibonacci method is an optimization method which can be used to find optimum of a 1D function (even discrete function) using elimination method. For use this method the initial interval of uncertainty, in which the optimum lies, has to be known. In addition the objective function should be unimodal, which has just an optimum solution in initial interval.
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Size: 1024 |
Author: serat.iej |
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Description: 简单绘制出常见标准benchmark函数的二维网格图，清晰的看出函数的最优值和局部最优，是单峰还是多峰函数-Simple map out common standard benchmark function of two-dimensional grid graph, clear see function of the optimal value and local optimum, is unimodal or multimodal function
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Size: 4096 |
Author: 鲁娟 |
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Description: 单目标测试函数 单峰的多峰的 很多个matlab-Single-objective test functions unimodal the multimodal many matlab
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Size: 5120 |
Author: wangminglin |
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Description: 进退法找求单峰区间，黄金分割法找最优解的matlab程序。-The advance and retreat method to find requirements unimodal interval, golden section method matlab program to find the optimal solution.
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Size: 1024 |
Author: litong |
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Description: 单参数单峰函数遗传算法求解最大值我自己写的一个例子-Single-parameter genetic algorithm unimodal function max I wrote an example
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Size: 1024 |
Author: ding liang |
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Description: PSO测试函数代码，包括单峰和多峰函数。-PSO test function code, including unimodal and multimodal function.
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Size: 8047616 |
Author: 徐夏 |
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Description: CEC2005测试源代码，可测试优化算法的性能，单峰，多峰，混合函数。-CEC2005 test source code, you can test the performance of optimization algorithms, unimodal, multimodal, mixed function.
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Size: 3310592 |
Author: 杨睿昕 |
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Description: 多元优化 单峰目标函数 多峰目标函数 遗传算法 matlab源码- multivariate optimization, Unimodal objective function, multimodal objective function, genetic algorithm ,matlab source
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Size: 1024 |
Author: 卫芬 |
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Description: 精密机械优化算法，格点法，针对单峰函数，实际优化中起到很好的作用，值得学习-Precision mechanical optimization algorithm, grid method, play a good role for unimodal functions, the actual optimization, it is worth learning
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Size: 102400 |
Author: lihao |
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Description: 黄金分割法，基于精密机械的优化算法，是单峰函数中保证精度要求的很好算法，应当掌握-Golden section method, based on precision machinery optimization algorithm is unimodal functions to ensure good precision algorithm should grasp
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Size: 103424 |
Author: lihao |
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Description: 类间方差法对噪音和目标大小十分敏感，它仅对类间方差为单峰的图像产生较好的分割效果。
当目标与背景的大小比例悬殊时，类间方差准则函数可能呈现双峰或多峰，此时效果不好，但是类间方差法是用时最少的。-Variance between class size of the noise and the target is very sensitive, it only to the between class variance to unimodal images produce better segmentation effect.
The disparity between the target and the background when the size ratio, the between class variance criterion function may present Shuangfeng or multi peaks, the effect is not good at this time, but the between class variance method is used when the least.
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Size: 660480 |
Author: 玉溪 |
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Description: 利用遗传算法的选择、交叉、变异功能来解决多元单峰函数求最优值问题-The use of genetic algorithm selection, crossover and mutation function to solve the multi-function uation unimodal optimal value problem
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Size: 1024 |
Author: 沉淀 |
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