Description: Matlab在图像处理与目标识别方面的应用实验程序示例。包括三个程序以及详细文档：一、染色体识别与统计，二、汽车牌照定位与字符识别，三、基于BP神经网络识别字符的简单实验。-Matlab in image processing and object recognition on the application of experimental procedures example. Including the three procedures and the detailed documentation : one chromosome to identify and statistics, two vehicle license positioning and character recognition, 3, BP neural network-based character recognition simple experiment. Platform: |
Size: 1249853 |
Author:林健 |
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Description: 用遗传算法解决通信中的TDOA问题
文件名 program
完成功能 求出在进行account_test次的试验中每一次的最优染色体，并且求出均值MV，和均方误差MSE
文件名 definition_constant( )
完成功能 对各个常量试验参数进行设定
文件名 main_program
完成功能 完成一次试验的计算
文件名 all_Noise
完成功能 计算TDOA值（由基站所测量的TDOA（受到噪声的干扰）)
文件名 gen_ini_pop_arr
完成功能 产生染色体矩阵pop_arr，矩阵的1，2行为估计的x，y坐标，矩阵的3，4行为0。-using genetic algorithms to solve the communication problems TDOA documents were obtained functional program completed during account_test meeting the test of the optimal every chromosome, and calculated average MV, and the mean square error MSE definition_constant file name () function to complete all regular Experimental parameters set main_program documents were completed functional testing of a complete calculation File Name all_Noise complete functional calculation TDOA value (measured from the base station TDOA (subject to noise interference )) File Name gen_ini_pop_arr have completed functional matrix pop_arr chromosome, the matrix acts estimated 1,2 x, y coordinates, and the matrix acts 3,4 0. Platform: |
Size: 3072 |
Author:田园 |
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Description: ％ [BestPop,Trace]=fmaxga(FUN,LB,UB,eranum,popsize,pcross,pmutation)
％ Finds a maximum of a function of several variables.
％ fmaxga solves problems of the form:
％ max F(X) subject to: LB <= X <= UB
％ BestPop--------最优的群体即为最优的染色体群
％ Trace----------最佳染色体所对应的目标函数值
％ FUN------------目标函数
％ LB-------------自变量下限
％ UB-------------自变量上限
％ eranum---------种群的代数,取100--1000(默认1000)
％ popsize--------每一代种群的规模；此可取50--100(默认50)
％ pcross---------交叉的概率,此概率一般取0.5--0.85之间较好(默认0.8)
％ pmutation------变异的概率,该概率一般取0.05-0.2左右较好(默认0.1)
％ options--------1×2矩阵,options(1)=0二进制编码(默认0),option(1)~=0十进制编码,option(2)设定求解精度(默认1e-4)- [BestPop, Trace] = fmaxga (FUN, LB, UB, eranum, popsize, pcross, pmutation) Finds a maximum of a function of several variables. Fmaxga solves problems of the form: max F (X) subject to : LB <= X <= UB BestPop-------- optimal chromosome groups is the best group Trace---------- chromosome corresponding to the best objective function value FUN------------ objective function LB------------- variable lower limit since the UB------------- variable upper limit eranum--------- populations algebra, take 100- 1000 (default 1000) popsize-------- population size of each generation this desirable 50- 100 (default 50) pcross--------- crossover probability, the probability of a general check 0.5- 0.85 between the better (default 0.8) pmutation------ mutation probability, the probability of 0.05 general admission better about-0.2 (default 0.1) options-------- 1 × 2 matrix, options (1) = 0 binary code (default 0), option (1) ~ = 0 decimal coding, option (2 ) set accuracy (default 1e-4) Platform: |
Size: 3072 |
Author:mmcc |
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Description: 使用遗传算法解决MTSP问题的一种新的染色体设计-The use of genetic algorithms to solve the MTSP problem the design of a new chromosome Platform: |
Size: 191488 |
Author:pengchao |
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Description: 林健写的Matlab在图像处理与目标识别方面的应用实验，包括染色体识别与统计、汽车牌照定位与字符识别、基于BP神经网络识别字符的简单实验。-Lam Kin Writing at the Matlab image processing and target recognition application experiments, including chromosome identification and statistics, vehicle license positioning and character recognition, based on BP neural network easy to identify characters in the experiment. Platform: |
Size: 1179648 |
Author:王云 |
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Description: 在matlab中完成染色体识别与统计，汽车牌照定位与字符识别两个图像处理方面的应用，步骤清晰，解释详尽，值得学习！-Matlab completed in chromosome identification and statistics, motor vehicle license character recognition and positioning of two image processing applications, these clear, detailed explanation, it is worth learning! Platform: |
Size: 1272832 |
Author:阿黄 |
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Description: 很详细地介绍了matlab在图像处理中的应用，其中有车牌号的识别，染色体的识别等，还有文档说明，精心整理的，希望和大家分享！-Very detailed description of the matlab in image processing applications, including license plate number recognition, chromosome identification, as well as documentation and careful finishing, and would like to share! Platform: |
Size: 1388544 |
Author:陈濛 |
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Description: DNA description based on matlab programming. It s able to distinguish the gain or loss section of each chromosome Platform: |
Size: 51200 |
Author:paul |
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Description: 染色体配对程序，先通过分割算法分割出单个染色体，在利用染色体的面积、周长、骨架来进行配对。-Chromosome pairing procedure, the first segmentation algorithm segmented by a single chromosome, chromosome in the use of the area, perimeter, skeleton matching. Platform: |
Size: 230400 |
Author:shuzhenqiu |
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Description: Matlab在图像处理与目标识别方面的应用 附有例题 1染色体识别与统计 2汽车牌照定位与字符识别 3 基于BP神经网络识别字符的简单实验-Matlab image processing and target recognition in the application of a chromosome with Example 2 License Plate Recognition and Statistical location and character recognition based on BP neural network to recognize three characters in a simple experiment Platform: |
Size: 1185792 |
Author:陶淘 |
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Description: 排课问题是一个有约束的、多目标的组合优化问题，并且已经被证明是一个NP完全问题。
遗传算法借鉴生物界自然选择和自然遗传机制，使用群体搜索技术，尤其是用于处理传统搜索方法难以解决的复杂的和非线性的问题。经过近40年的发展，遗传算法在理论研究和实际应用中取得了巨大的成功，本文将遗传算法用于排课问题的求解，首先讨论了排课问题中的影响因素、主要约束条件、求解目标和难点，并用数学模型完整地描述了排课问题。其次对多个模糊排课目标进行了定量分析，建立了排课优化目标空间。针对排课问题研究了染色体编码方式以及遗传算子的设计，提出了适应度函数的计算方法。最后对排课问题进行了实验。实验结果表明，其过程的目标值跟踪显示，算法稳健趋优，所得结果令人满意。-Course Scheduling problem is a constrained, multi-objective optimization problem, and has proven to be a NP complete problem.
Genetic algorithms reference biosphere and the natural genetic mechanism of natural selection, using the group search technology, particularly the traditional search methods for handling complex and difficult to solve nonlinear problems. After nearly 40 years of development, the genetic algorithm in the theoretical study and practical application was a great success, this paper genetic algorithm for solving the course timetabling problem, first discussed the impact of factors in the course arrangement, the main constraints, to solve goals and difficulties, and a complete mathematical model to describe the course arrangement. Arranging multiple fuzzy goals followed by a quantitative analysis, the optimal target Arranging space. Arranging for the Study of the chromosome coding and genetic operators design, proposed fitness function is calculated. Finally, the co Platform: |
Size: 1290240 |
Author:张林杰 |
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Description: Matlab在图像处理与目标识别方面的应用实验程序示例。包括三个程序以及详细文档：一、染色体识别与统计，二、汽车牌照定位与字符识别，三、基于BP神经网络识别字符的简单实验-Matlab image processing and target recognition in the application of experimental procedures for example. Consists of three procedures, and detailed documentation: a, chromosome identification and statistics, two license plate location and character recognition, 3, based on BP neural network character of the simple experiment Platform: |
Size: 123904 |
Author:刘谋鑫 |
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Description: 基于MATLAB的遗传算法。遗传算法是以自然选择和遗传理论为基础，将生物进化过程中适者生存规则与群体内部染色体的随机信息交换机制相结合算法。它提供了一种求解非线性、多模型、多目标等复杂系统优化问题的通用框架。-MATLAB Genetic Algorithms. Genetic algorithm based on natural selection and genetic theory, the process of biological evolution and the survival of the fittest rules of random information exchange mechanism within the group chromosome combined algorithm. It provides for solving nonlinear, multi-model, multi-objective optimization problems of complex systems such as a common framework.
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Size: 9704448 |
Author:梁家理 |
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Description: 遗传算法
1、评估每条染色体所对应个体的适应度
2、遵照适应度越高，选择概率越大的原则，从种群中选择两个个体作为父方和母方
3、抽取父母双方的染色体，进行交叉，产生子代
4、对子代的染色体进行变异
5、重复2，3，4步骤，直到新种群的产生。结束循环。(1. Evaluate the fitness of each chromosome.
2. Following the principle of higher fitness and greater probability of selection, two individuals are selected from the population as the parent and the parent.
3. Extract the chromosomes of both parents and cross them to produce offspring.
4. Mutation of the chromosomes of the progeny
5, repeat 2, 3, 4 steps until the new population is born. End the cycle.) Platform: |
Size: 6144 |
Author:北境乌鸦 |
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Description: 遗传算法，模拟达尔文进化论的自然选择和遗产学机理的生物进化构成的计算模型，一种不断选择优良个体的算法。谈到遗传，想想自然界动物遗传是怎么来的，自然主要过程包括染色体的选择，交叉，变异（不明白这个的可以去看看生物学），这些操作后，保证了以后的个基本上是最优的，那么以后再继续这样下去，就可以一直最优了。利用遗传算法，实现三维点云的配准。(Genetic algorithm, a computational model that simulates the biological evolution of Darwin's evolutionary theory of natural selection and inheritance mechanism, is an algorithm that continuously chooses good individuals. When it comes to inheritance, think about how animal inheritance comes from in nature. The main natural processes include chromosome selection, crossover, mutation (if you don't understand this, you can look at biology). These operations ensure that the next one is basically optimal, and then continue to do so in the future, you can always be optimal.) Platform: |
Size: 2190336 |
Author:秋水不染成 |
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Search - chromosome matlab