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介绍了神经 网络中的HOPFIELD算法的C语言实现.
介绍了神经 网络中的HOPFIELD算法的C语言实现.-Introduce a neural network algorithm HOPFIELD realize the C language.
- 2022-02-02 02:12:00下载
- 积分:1
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《基于MATLAB系统分析与设计--神经网络》一书的源程序
《基于MATLAB系统分析与设计--神经网络》一书的源程序-"based on MATLAB analysis and design-- neural networks," a book of the source
- 2022-07-22 23:17:59下载
- 积分:1
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介绍了神经 网络中的BPN算法的C语言实现.
介绍了神经 网络中的BPN算法的C语言实现.-Introduce a neural network BPN algorithm C language.
- 2022-08-07 15:15:25下载
- 积分:1
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Use of MFC technology to realize ant colony algorithm and genetic algorithm, vis...
采用MFC技术,实现蚁群算法和遗传算法,形象化了算法实现的过程,有助于我们的学习和理解。-Use of MFC technology to realize ant colony algorithm and genetic algorithm, visualization of the algorithm implementation process, contribute to our learning and understanding.
- 2023-03-15 16:55:04下载
- 积分:1
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神经网络机器人避障matlan仿真程序可以模拟技术。
神经网络机器人避障matlan仿真程序
可模拟机器人在空间的避障动作-Neural Network Robot Obstacle Avoidance matlan simulation program can simulate the robot moves in space, obstacle avoidance
- 2022-03-05 19:28:56下载
- 积分:1
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有关神经网络的源码
有关神经网络的源码-the neural network source
- 2022-02-13 10:29:45下载
- 积分:1
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专家系统课程设计,用计算机解决SP先生谜题,有详细代码
专家系统课程设计,用计算机解决SP先生谜题,有详细代码-curriculum design expert system, computer SP Mr. Mystery solved a detailed code
- 2023-08-02 23:10:03下载
- 积分:1
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Using Particle Swarm solution to TSP (traveling salesman) problems, in accordanc...
用粒子群方法解决TSP(旅行商)问题,按照TSP1.m中的格式输入程序参数即可-Using Particle Swarm solution to TSP (traveling salesman) problems, in accordance with the format in TSP1.m parameter input program
- 2022-04-19 19:23:42下载
- 积分:1
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这是一篇对PSO算法可以使用从事人工智能的学生…
这是一篇关于pso利用的文章 也许对搞人工智能的的同学有很大的用处-This is an article on the PSO may use to engage students in artificial intelligence have great usefulness
- 2022-03-30 23:04:33下载
- 积分:1
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微粒群算法与其它进化类算法相类似,也采用“群体”与“进化”的概念,同样也是依据个体(微粒)的适应值大小进行操作。所不同的是,微粒群算法不像其它进化算法那样对于个...
微粒群算法与其它进化类算法相类似,也采用“群体”与“进化”的概念,同样也是依据个体(微粒)的适应值大小进行操作。所不同的是,微粒群算法不像其它进化算法那样对于个体使用进化算子,而是将每个个体看作是在n维搜索空间中的一个没有重量和体积的微粒,并在搜索空间中以一定的速度飞行。-Particle swarm optimization algorithm with other similar type of evolution, but also the use of " groups" and " evolution" concept is also based on the individual (particle) size of the operation of fitness. The difference is that unlike other particle swarm optimization evolutionary algorithm as the use of evolution for the individual operator, but as each individual in the n-dimensional search space of a weight and size of the particles, and in the search space the speed of a certain flight.
- 2023-05-18 16:45:03下载
- 积分:1