PSOMADS0

说明：  用数值积分算法计算hankel变换,并采用连分式逼近(Hankel transform by continued fraction)

粒子群算法源代码,属于进化算法的一种，和遗传算法相似，它也是从随机解出发，通过迭代寻找最优解。(Particle swarm algorithm source code, is a kind of evolutionary algorithm, and genetic algorithm are similar, it is also starting from the random solutions, through the iterative search for the optimal solution.)

Contacts Settings Test extends Instrumentation Test Case.

用于求解单目标优化问题的正弦余弦算法。 SCA创建多个初始随机候选解决方案，并要求它们使用基于正弦和余弦函数的数学模型向外波动或朝向最佳解决方案。几个随机和自适应变量也被集成到该算法中，以强调在不同的优化里程碑中探索和利用搜索空间。 压缩包包括：发表的论文、优化算法代码、优化工具箱。(Sine-cosine algorithm for solving single objective optimization problems. SCA creates multiple initial random candidate solutions and requires them to use mathematical models based on sinusoidal and cosine functions to fluctuate outward or towards the best solution. Several random and adaptive variables are also integrated into the algorithm to emphasize exploring and utilizing search space in different optimization milestones. Compression packages include: published papers, optimization algorithm code, optimization toolbox.)

雷达截面积————————椭圆柱的后向散射RCS(backscattering RCS of Elliptical )

matalab的书籍，洗碗柜几点发的上课了几分快乐的vfdbfsvfdv (On dem good things and academic research can be used to offer you and progressive)

几个计算，叶面积指数的MATLAB程序。详情见其中说明。一共有三个小程序。(Several terms, leaf area index of the MATLAB program. Details are stated. A total of three procedures.)

关于turbo码状态转移的matlab仿真程序，详细描述的状态之间的转移关系(Turbo codes on the state transition of the matlab simulation program, a detailed description of the transfer of the state of the relationship between the)

该算法既保留了遗传算法的搜索特性，又利用了免疫算法的多机制求解多目标函数最优解的自适应特性，在很大程度上避免了“早熟”，收敛于局部极值。 生物体的免疫系统是一个高度进化、复杂的系统，它能自适应地识别和排除入侵肌体的抗原性异物，保护机体免受损害及维持内坏境稳定，并具有学习、记忆和自适应调节的能力。当抗原入侵时，免疫系统通过自体耐受对‘自己’和‘非己’进行识别，并产生最恰当的抗体排除抗原，通过抗体与抗体之间、抗原与抗体之间的相互刺激和抑制关系，降低抗原对免疫细胞的刺激，抑制抗体的过度分化、增殖，保证免疫平衡并维持抗体的多样性。同时在免疫过程中将产生抗体的部分细胞作为记忆细胞保存下来，对于今后侵入的同类抗原，相应的记忆细胞受到激发而产生大量的抗体。为提高生物体的免疫机能，医学上往往根据抗原性异物提取疫苗给生物体接种，接种过的生物体由于免疫细胞预先获得了抗原染色体的特征信息，因而在类似抗原入侵时，能迅速产生亲和度很高的抗体，有效抵御入侵。(The search algorithm only retains the characteristics of genetic algorithms, and use multiple mechanisms of immune algorithm for solving multi-objective characteristics of adaptive optimal solutions, in large part to avoid the " premature" , converge to local minima. Organism' s immune system is a highly evolved, complex system which adaptively identify and remove foreign matter intrusion antigenic body, protecting the body injury and maintain internal stability bad environment, and has learning, memory and adaptive Ability. When the antigen invasion of immune system tolerance to autologous ' own' and ' non-self' to identify and produce the most appropriate antigen antibody excluded by between antibody and antibody, antigen and antibody mutual stimulation and inhibition of the relationship between reduce the antigen to stimulate immune cells, antibodies inhibit excessive differentiation, proliferation, immune balance and ensure the maintenance of antibody dive)

Instance Base Learning example