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4下载:
利用遗传算法优化BP神经网络权值和阈值,然后进行训练,利用训练好的模型进行预估。附实例-The use of genetic algorithm to optimize BP neural network weights and thresholds, and then training, training a good use of forecast models. Attached examples
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地球物理开发包。地震处理、解释、反演等。C++编写,跨平台。-Geophysical Library is a C++-library to handle geophysical data. At the moment the focus is on magnetotelluric and seismic data. It also includes a genetic algorithm for data inversion, signal processing and statistics
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该文件是优秀论文并带有相应的源码。在Matlab软件平台上,对所提出的基于遗传算法的电力系统电力市场分段竞价交易算法进行了阶梯型报价曲线、线性报价曲线这两种常用报价曲线情况下的算例验证,计算结果显示算法的寻优效果因报价曲线性质的不同而略有区别,但两种情况均可得到优化的购电费用。实验结果证明了该算法应用于分段竞价模型的有效性和可行性,且不受报价曲线形式的限制。-The document is an excellent paper with a corresponding source code.
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Genetic algorithm to evolving a logic network of 16 gates, and graph evaulation for shortest path.
It use matlab ga basic function
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提供一种用matlab编写的遗传算法,用于电力系统的,解决最优模型-A genetic algorithm using matlab for power system, to solve the optimal model
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线性递减权重粒子群优化算法是从随机解出发,通过迭代寻找最优解,它也是通过适应度来评价解的品质,但它比遗传算法规则更为简单,它没有遗传算法的“交叉”(Crossover) 和“变异”(Mutation) 操作,它通过追随当前搜索到的最优值来寻找全局最优。这种算法以其实现容易、精度高、收敛快等优点引起了学术界的重视,并且在解决实际问题中展示了其优越性。 -Linear decreasing weight particle swarm optimization starting from random
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旅行商问题(TSP)是典型的NP完全问题,遗传算法是求解NP完全问题的一种常用方法。旅行商问题(TSP)的蚁群算法实现算法。在MATLAB中用遗传算法施行对TSP问题进行了求解,进行了选择、交叉和变异算子进行了算法设计。MATLAB源代码。-Traveling Salesman Problem (TSP) is a typical NP-complete problem, genetic algorithm for solving NP-complete problems, a common m
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快速遗传剩余静校正方法(FGRS)
关键词: 互相关剩余静校正 遗传算法剩余静校正 快速遗传剩余静校正方法 大剩余静校正量
复杂地质地区(如复杂山地、山前带等),在野外静校正、折射或层析静校正等之后,仍可能存在大剩余静校正量,影响叠加效果。转换波剩余静校正量往往也较大,是转换波地震资料处理的难题之一。针对上述问题,研发了快速遗传剩余静校正方法,其特点是:
地表一致性
组合算法(互相关+遗传算法)
非线性反演
快速高效
全局寻优
可解决大的纵波剩余静
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A code to call genetic algorithm handle for ANN weight optimization
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a powerful approach to find the
optimal size and location of distributed generation units in a
distribution system using Genetic Optimization algorithm (GA).
The total active and reactive power losses are minimized and
voltage profile is impr
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利用遗传算法对电动汽车充电统一管理进行优化,并得到优化前后的负荷功率曲线对比图及充电计划-Using genetic algorithm to optimize the unified management of electric vehicle charging, and optimize the power curve of load before and after contrast figure and charging projects
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用遗传算法求解电网规划问题,双层算法求解,上层为遗传算法,下层利用拉格朗日对偶线性化后求解(Genetic algorithm is used to solve the power grid planning problem, double-layer algorithm is used to solve the problem, the upper layer is genetic algorithm, and the lower layer is solved by Lagrange dua
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