搜索资源列表
jiyuyichuansuanfadelvboqiyouhuasheji
- 遗传算法是一种模拟自然界生物进化的搜索算法，由于它简单易行，鲁 棒性强，尤其是其不需要专门的领域知识而仅用适应度函数作评价来指导搜 索过程，从而使它的应用范围极为广泛，并且己在众多领域得到了实际应用， 取得了许多令人瞩目的成果，引起广大学者和工程人员的关注。- The genetic algorithm is a kind of searching method which simulates the natural evolution. It is simple and ea
eCheat.com_Topic_28071_20090627.txt
- evolution vs. adam and eve
article_37f
- ES D evolution strategies GA D genetic algorithm ...... One of the first applications of genetic algorithms in explained here -ES D evolution strategies GA D genetic algorithm ...... One of the first applications of genetic algorithms in explained
introductiontoec
- Elements of Evolution: – Reproduction – Random variation – Competition – Selection of contending individuals from a population. ● Evolutionary computation: computational methods simulating evolution, mostly used to find a solution in
scfdma.zip
- sc fdma for lte uplink in long term evolution ,sc fdma for lte uplink in long term evolution
evolution-game-matlab
- 一个演化博弈的小程序。非常有用。用matlab写的，非常非常有用。-a evolution game thoery simulation,a matlab program,it s very useful.really usefull,really really usefuly. kao,20 zifu?
A-PSO-method-with-nonlinear-time-varying-evolutio
- Abstract A particle swarm optimization method with nonlinear time-varying evolution (PSO-NTVE) is employed in designing an optimal PID controller for asymptotic stabilization of a pendubot system. In the PSO-NTVE method, parameters are determ
2
- Long Term Evolution Downlink Physical Layer Simulation in Matlab and Simulink
Multi-objective-genetic-algorithm
- Real world problems often present multiple, frequently conflicting, objectives. The research for optimal solutions of multi-objective problems can be achieved through means of genetic algorithms, which are inspired by the natural process of evo
SMC2
- In this paper, the steady-state behaviour of discretized terminal sliding mode control is studied. A discrete terminal sliding mode control is designed by discretizing the continuous-time system and then the steady-state behaviour is analysed in term
ga
- The genetic algorithm is a method for solving both constrained and unconstrained optimization problems that is based on natural selection, the process that drives biological evolution. The genetic algorithm repeatedly modifies a population of individ
My-Book
- My Final Project : Learning Media Design of LTE (Long Term Evolution) Network Planning based on Android
New-WinRAR-ZIP-archive
- The purposed approach utilizes Differential Evolution (DE) to optimize an image processing chain which has successfully been used to segment breast ultrasound and X-ray lung images. The training is based on three sample images provided by an expert.