OPenCV written using a hough transform line detection procedure

改进遗传算法在TSP中的应用!很好用哦!-Improved Genetic Algorithm in TSP application! Good use Oh!

用c语言编写的粒子群算法程序，下载后可以直接使用-With the c language of the particle swarm optimization program, download can be used directly

遗传算法学习资料-GA learning materials

命题逻辑中的推理规则可以用来证明一个已经表示成命题公式的定理，但它还不便于机械化实施。因为其中的各条规则都未指明在推导的什麽步骤上应该引入什麽前提或中间结论，这些还有赖于人的经验技巧和才能。1960年王浩提出的算法，可以完全脱离人的经验和技巧，机械地构造每一步推导，证明一个命题逻辑定理的成立。 -Propositional logic in the inference rule can be used to prove that a propositional formula has been expressed as the theorem, but it is not easy to implement mechanization. Because the rules did not specify what steps in the derivation of what should be the introduction of the premise or intermediate conclusions, which also depends on the person s experience of the skills and talent. Wang Hao in 1960 proposed algorithm can be completely divorced from the person s experience and skills, a mechanical structure is derived for each step to prove that a propositional logic theorem establishment.

use swarm intelligence to simulate network routings in omnet-use swarm intelligence to simulate networ k routings in omnet

基于人工神经网络的房地产项目评判模型，值得一看-based on artificial neural network evaluation model for real estate projects, an eye-catcher

遗传算法,实现的是一个猜答案的过程， 这种算法比较经典，可以借鉴-genetic algorithm to achieve guess the answer is a process, this method is classic, we can draw on

基于隐马尔可夫模型的人脸识别源代码,是作模式识别的最好学习代码-Hidden Markov Model-based face recognition source code for pattern recognition is the best learning code

加法难题 有如下的加法算式： donald + gerald = robert 每个字母代表一个不同的数字(0-9)，你能否求出每个字母分别代表什么数字？-Adder problems with the additive formula is as follows : donald gerald = robert each letter representing a different figures (0-9), Can you calculated each letter on behalf of what?

首先采用某种编码方式将解空间映射到编码空间，每个编码对应问题的一个解，称为染色体或个体。一般通过随机方法确定起始的一群个体，称为种群，在种群中根据适应值或某种竞争机制选择个体，使用各种遗传操作算子产生下一代如此进化下去，直到满足期望的终止条件。-begin using some form of coding mapping to the solution space coding space, each encoding a corresponding solution to the problem, known as chromosome or individual. General randomly determined by the initial group of individuals, called stocks, the stocks based on fitness or some mechanism to choose the individual competition, the use of genetic Operator evolution of the next generation so on, until the termination meet expectations conditions.