Description: 遗传算法（Genetic Algorithm）是模拟达尔文生物进化论的自然选择和遗传学机理的生物进化过程的计算模型，是一种通过模拟自然进化过程搜索最优解的方法，-Genetic Algorithm (Genetic Algorithm) is a simulation of Darwinian biological evolution, natural selection and genetic mechanism of the process of biological evolution computing model, is a simulation of natural evolutionary processes through the optimal solution search methods, Platform: |
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Author:张正荣 |
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Description: 提出一种改进的遗传算法用于求解机械手运动学逆问题. 该算法采用实数编码, 其交叉概率和变异
概率根据解的适应度函数值自适应调整. 计算机仿真结果显示, 该算法较简单遗传算法(SGA) 求解精度高,
收敛速度快且稳定性能好.-An improved genetic algorithm for solving the inverse problem of manipulator kinematics. The algorithm uses real number encoding, the crossover probability and mutation probability according to the fitness function value of solution adaptive. Computer simulation results show that the algorithm is relatively simple genetic algorithm for (SGA) for solving high precision, fast convergence and stable performance is good. Platform: |
Size: 143360 |
Author:杨元龙 |
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Description: ：为了提高最小二乘支持向量回归机的性能，将Morlet小波核函数引入其中，形成了最小二乘小波支
持向量回归机模型。利用待优化的参数重构模型的目标函数和约束条件，并在此基础上通过遗传算法进行参数
选择，从而提高了该模型的泛化能力。将最小二乘小波支持向量回归机应用于导弹陀螺仪的漂移趋势预测，仿真
实验结果表明了该方法的有效性和可行性，因此可以为陀螺仪的故障预报、可靠性辅助决策提供依据。-To improve the ability of least square support vector regression algorithm，a least square wavelet
support vector regression model by introducing the Morlet wavelet kernel is presented．The object function and
constraint condition are reconstructed by the parameters to be optimized．On the base of it，the model parame—
ters are optimized through genetic algorithm．As a result，the model attains the better generalization ability．
The least square wavelet support vector regression model is used tO forecast the missile gyroscope’S drift tend—
ency．The simulation experiment results indicate the feasibility and validation of the algorithm．So it can provide
basis for the gyroscope’S fault prediction and reliability aid decision． Platform: |
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Author:11 |
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Description: 一种基于遗传算法的盲分离方法的文章，给出的仿真效果。-Based on genetic algorithm approach for blind separation of the article gives the simulation results. Platform: |
Size: 191488 |
Author:陈宏 |
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Description: 遗传算法是一种大致基于模拟进化的学习方法
假设通常被描述为二进制位串，也可以是符号表达式或计算机程序搜索合适的假设从若干初始假设的群体或集合开始当前群体的成员通过模拟生物进化的方式来产生下一代群体，比如随机变异和交叉
-Genetic algorithm is a general simulation-based evolutionary learning method assumes that is often described as a binary bit string, it can be a symbolic expression or a computer program searches for a suitable assumptions from a number of groups or a collection of the initial assumptions the current members of the group began by simulating the way biological evolution to produce the next generation of groups, such as random mutation and cross - Platform: |
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Author:ljg123456 |
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Description: 这是一篇来自哈尔滨工业大学的关于应用遗传算法来优化模糊规则的论文，该论文于2005年1月发表于计算机仿真期刊。文中比较系统的介绍了遗传算法的基本知识、模糊推理机制以及应用遗传算法来优化模糊规则的步骤，最后给出比较好的仿真结果。-It is one from the Harbin Institute of Technology on the application of genetic algorithms to optimize the fuzzy rules of the thesis, the thesis in January 2005 published in the Journal of Computer Simulation. Paper, a more systematic introduction to the basics of genetic algorithms, fuzzy inference mechanism and the genetic algorithm to optimize the fuzzy rules of procedure, given good simulation results. Platform: |
Size: 226304 |
Author:haphan |
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Description: 遗传算法（Genetic Algorithm）是模拟达尔文生物进化论的自然选择和遗传学机理的生物进化过程的计算模型，是一种通过模拟自然进化过程搜索最优解的方法-Genetic algorithm (Genetic Algorithm) is a simulation of Darwinian evolution, natural selection and genetic mechanism of the calculation model of biological evolution is a natural evolutionary process through the simulation method of searching the best Platform: |
Size: 3920896 |
Author:zsy |
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Description: 免疫记遗传算法在TSP中的应用，经实验仿真，发现本方法快速有效-Immune genetic algorithm in TSP in mind the application of the experimental simulation, found that this method is rapid and effective Platform: |
Size: 7168 |
Author:曾行 |
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Description: 设计特定的进化操作或约束修正因子。文献[ 28 ]采用罚函数法,利用非固定多段映射罚函数对约束优化问题进行转化,再利用PSO求解转化后的问题,仿真结果显示PSO相对进化策略和遗传算法有优越性,但其罚函数的设计过于复杂,不利于求解-Operation or design of the evolution of specific binding correction factor. Literature [28] The penalty function method, using non-stationary multi-stage fine mapping function to transform constrained optimization problem, and then transformed using PSO to solve the problem, simulation results show that PSO is relatively evolution strategy and genetic algorithm has advantages, but the penalty function The design is too complex and not conducive to solving Platform: |
Size: 2048 |
Author:杨科 |
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Description: 用二进制遗传算法解决函数的极小值问题，用MATLAB进行仿真，设和初学者-Function of the binary genetic algorithm with the minimum of the problem, with the MATLAB simulation, design and beginners Platform: |
Size: 26624 |
Author:yangdanxuan |
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Description: 遗传算法（Genetic Algorithm）是模拟达尔文生物进化论的自然选择和遗传学机理的生物进化过程的计算模型，是一种通过模拟自然进化过程搜索最优解的方法-Genetic Algorithm (Genetic Algorithm) is a simulation of Darwinian biological evolution and genetic mechanism of natural selection process of model evolution is a process by simulating natural evolution search the optimal solution method Platform: |
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Author:sun |
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Description: 应用遗传算法解决旅行商问题，其中在本程序中是10个城市的TSP，并仿真结果表明本例中遗传算法各个环节所采用的方法都是先进而有效的。-Application of genetic algorithm to solve traveling salesman problem, which is in the program in 10 cities TSP, and simulation results show that the genetic algorithm in this case all aspects of the methods used are advanced and effective. Platform: |
Size: 2048 |
Author:李海霞 |
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Description: 人工神经网络(Artificial Neural Network)是从生理角度对智能的模拟，具有极
高的学习能力和自适应能力，能够以任意精度逼近任意函数，完成对系统的仿真；
而遗传算法是对自然界生物进化过程的模拟，具有极强的全局寻优能力，这两种
算法都是当下研究较多的智能方法。将这两种方法与常规的 PID 控制相结合，
构成智能 PID 控制器，使其具有参数自整定、自适应的能力，以适应复杂环境
下的控制要求，这一思路对提高控制效果具有很好的现实意义。
-Artificial Neural Network (ANN) is an imitation of the intelligence by the point of physiological. It has a high capacity of learning and adaptive, can approximate any function to arbitrary accuracy, and complete the simulation of the system. The Genetic
algorithm is a simulation of natural biological evolution, which has a strong ability of
global optimization. These two algorithms are more intelligent method of current
research. The idea of combining these two methods with the conventional PID
controller to be a intelligent controller with the abilities of parameter auto-tuning and
adaptive for the requirements of the complex environment, has a high practical
significance of improving the control effect.
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Author:baijiaxuan |
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Description: 借助胞腔, 并利用遗传算法能够最终收敛于非线性多峰函数全局最优解的特点, 动态
地剖分和排除胞腔, 从而构成一种新型遗传算法——胞腔排除遗传算法, 利用该算法可求取非
线性多峰函数全部全局最优解。仿真实验表明该算法合理、有效。-With cell cavity, and the use of genetic algorithms will eventually converge to the nonlinear multimodal function global optimum characteristics, dynamic partitioning and rule out the cell cavity, so as to constitute a new type of genetic algorithms- genetic algorithm for cell excluding the use The algorithm can strike all the non-linear multimodal function global optimal solution. Simulation results show that the algorithm is reasonable and effective. Platform: |
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Author:赵 |
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Description: 为寻求复杂多峰函数的全局最优解问题, 提出了新型混合算法。该算法由带共享函数
的遗传算法、移民技术、聚类算法和改进的Pow ell 算法组成。由于上述算法的有机配合, 提高了
混合算法的全局和局部搜索能力。油藏系统应用实例和仿真实例证明了算法的有效性-Complex multimodal function to find a global optimal solution of problem, a new hybrid algorithm. The algorithm functions by a genetic algorithm with sharing, migration technology, clustering algorithm and the improved algorithm is composed of Pow ell. As the organic with the above algorithm, a hybrid algorithm to improve the global and local search capabilities. Reservoir system application examples and simulation results demonstrate the effectiveness of the algorithm Platform: |
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Author:赵 |
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Description: 本文研究了多峰优化问题, 利用梯度算子和筛选策略, 得到了一种可求解多峰函数
全部最优解的改进型遗传算法. 数值模拟结果表明, 该算法在处理复杂多峰函数优化问题时, 局
部搜索能力和克服过早收敛能力方面相对于传统遗传算法均有很大提高.-In this paper, multimodal optimization problems, the use of gradient operator and screening strategies can be solved by a multi-modal function all improved genetic algorithm for optimal solution. Numerical simulation results show that the algorithm in dealing with complex multi-modal function optimization problem , the local search ability and capacity to overcome the premature convergence of genetic algorithms are compared with the traditional greatly improved. Platform: |
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Author:赵 |
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Description: 针对BP神经网络存在的缺点，本文利用遗传算法能够收敛到全局最优解而
且遗传算法鲁棒性强的特点将遗传算法同神经网络结合起来，不仅能发挥神经网
络的泛化映射能力，而且使神经网络具有很快的收敛性以及较强的学习能力。为
了验证遗传算法优化BP神经网络的有效性，本文将此算法应用到直线一级倒立
摆的稳定控制中，同时利用UbVIEW语言界面开发能力强，并且数据输入、网
络通信、硬件控制简单的优点，制作了倒立摆的仿真控制和实时控制软件。仿真
研究表明，遗传算法优化BP神经网络的控制器设计是可行的，可以很好的实现倒
立摆的稳定控制。
-BP neural network for the shortcomings, this paper genetic algorithm can converge to global optimal solution and
And genetic algorithm robustness characteristics of the genetic algorithm combined with neural networks, neural networks can not only play
The generalization ability of network mapping, and the neural network with fast convergence and a strong ability to learn. As
The validation of genetic algorithm to optimize the effectiveness of BP neural network, this algorithm is applied to this line a handstand
Put stability control, and interface development using UbVIEW language ability, and data entry, network
Network communications, hardware, the advantages of simple control, produced a simulation of the inverted pendulum control and real-time control software. Simulation
Studies have shown that genetic algorithm BP neural network controller design is feasible, can achieve a good fall
Li put stability control.
Platform: |
Size: 4796416 |
Author:高飞 |
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Search - genetic algorithm simulation