搜索资源列表
MK
- Mann-Kendall突变检验方法，有点事不需要样本遵从一定的分布，也不受少量异常值的干扰，文件包内附例子。-Mann-Kendall mutation testing methods, some must do Do not need to comply with the distribution of samples, are not subject to interference from a small number of outliers, documents containing
tspmatlab
- 提出一种改进的禁忌搜索算法来求解背包问题。该算法基于禁忌搜索技术,并采用I&D策略,同时设计了两种针对局 部最优解的变异算子。改进后的算法能有效地弥补标准禁忌算法对初始解依赖的缺陷,同时也避免了搜索停滞的现象。通过对具 体实例和随机问题的测试,表明改进后的禁忌搜索算法有更好的性能。 关-An improved tabu search algorithm to solve knapsack problem. The algorithm is based on tabu
tsp
- 该程序解决10个城市的货郎担问题（TSP），主要使用简单的遗传算法实现。该过程中包括：编码、解码，选择，交叉，变异等！-The program to solve the traveling salesman problem of 10 cities (TSP), the use of simple genetic algorithm. The process includes: encoding, decoding, selection, crossover and mutation!
ModelGenerationforanIntrusionDetection
- 记载每一代的进化过程中保留多个最优个体不参加交叉，变异等遗传运算，而直接将他们复制到下一代群体中。-Documented the evolution of each generation to keep more than the best individual does not participate in crossover and mutation genetic operators, and direct them to the next generation of copy group
multiobjectiveoptimization
- 文中运用matlab实现了多目标问题的求解，实现过程涉及了GA算法的求解，交叉变异等操作均有详细的步骤。-Matlab applied to achieve a multi-objective problem solving process involving the GA algorithm solving crossover and mutation operations are detailed steps.
JSMutationEvent
- JS Mutation Event for Linux Web Interface Manager.
MutationEvent
- Mutation Event Source Code for Linux.
gasample
- 基本遗传算法的C语言实现，由用户输入繁衍世代数、交叉率、变异率、随机数等内容，经过遗传变异等，得出最佳个体的所在代数及其他相关信息。-Basic genetic algorithm C language, multiply the number of generations, crossover rate, mutation rate, a random number and other content entered by the user, through genetic mutation,
yichuansuanfa
- 包含了遗传算法的基本功能，实现了变异，交叉等操作，适合初学者学习。-Contains the basic functions of the genetic algorithm to achieve a mutation, crossover operation, suitable for beginners to learn.
4
- 同生命科学中的免疫理论类似，免疫算子也分两种类型：全免疫和目标免疫，二者分别对应于生命科学中的非特异性免疫和特异性免疫。其中，全免疫是指群体中每个个体在变异操作后，对其每一环节都进行一次免疫操作的免疫类型；目标免疫则指个体在进行变异操作后，经过一定判断，个体仅在作用点处发生免疫反应的一种类型。-Life sciences with similar immune theory, immune operator can be divided into two types: full immunity
PID
- 免疫粒子群算法用于PID整定。采用线性惯性系数，自适应交叉变异方法-Immune Particle Swarm Optimization for PID tuning. Linear inertia coefficient, adaptive crossover mutation method
fwdlabexperiments
- NETWORKING LAB PROGRAMS In this paper, we use a wireless sensor network with 100 unknown nodes, which are randomly produced and uniformly distributed in a square region of 5R*5R. Assuming that all nodes are located in the first quadrant, the l