This program is distributed in the hope that it will be useful, ** but WITHOUT ANY WARRANTY without even the implied warranty of ** MERCHANTABILITY or Fitness FOR A PARTICULAR PURPOSE. See the ** GNU General Public License for more details.
标签： distributed WARRANTY program WITHOUT
上传时间： 2016-01-11
上传用户：thesk123
/* This a simple genetic algorithm implementation where the */ /* evaluation function takes positive values only and the */ /* Fitness of an individual is the same as the value of the */ /* objective function
标签： implementation evaluation algorithm function
上传时间： 2016-01-18
上传用户：wkchong
// Copyright (c), Philips Semiconductors Gratkorn // (C)PHILIPS Electronics N.V.2000 // All rights are reserved. // Philips reserves the right to make changes without notice at any time. // Philips makes no warranty, expressed, implied or statutory, including but // not limited to any implied warranty of merchantibility or Fitness for any //particular purpose, or that the use will not infringe any third party patent, // copyright or trademark. Philips must not be liable for any loss or damage // arising from its use.
标签： Semiconductors Electronics Copyright Gratkorn
上传时间： 2016-02-04
上传用户：xuanjie
THIS DESIGN IS PROVIDED TO YOU "AS IS". XILINX MAKES AND YOU RECEIVE NO WARRANTIES OR CONDITIONS, EXPRESS, IMPLIED, STATUTORY OR OTHERWISE, AND XILINX SPECIFICALLY DISCLAIMS ANY IMPLIED WARRANTIES OF MERCHANTABILITY, NON-INFRINGEMENT, OR Fitness FOR A PARTICULAR PURPOSE. This design has not been verified on hardware (as opposed to simulations), and it should be used only as an example design, not as a fully functional core. XILINX does not warrant the performance, functionality, or operation of this Design will meet your requirements, or that the operation of the Design will be uninterrupted or error free, or that defects in the Design will be corrected. Furthermore, XILINX does not warrant or make any representations regarding use or the results of the use of the Design in terms of correctness, accuracy, reliability or otherwise.
标签： CONDITIONS WARRANTIES YOU PROVIDED
上传时间： 2016-03-21
上传用户：1427796291
实现了一个简单的花朵进化的模拟过程。 花朵的种群数量是10，共进化了50代。 通过运行程序，你会发现通过不断的进化，种群的总的适应环境的能力在逐步提高（Fitness的值下降）。
上传时间： 2013-12-20
上传用户：缥缈
A dissipative particle swarm optimization is developed according to the self-organization of dissipative structure. The negative entropy is introduced to construct an opening dissipative system that is far-from-equilibrium so as to driving the irreversible evolution process with better Fitness. The testing of two multimodal functions indicates it improves the performance effectively. structure. The negative entropy is introduced to construct an opening dissipative system that is far-from-equilibrium so as to driving the irreversible evolution process with better Fitness. The testing of two multimodal functions indicates it improves the performance effectively.
标签： self-organization optimization dissipative developed
上传时间： 2016-03-31
上传用户：zgu489
基于多线程机制的，利用Matlab编写，粒子群优化算法。目标变量采用归一化处理，适用于所有的优化函数。优化函数自定义为Fitness(x)。
上传时间： 2013-12-30
上传用户：banyou
个程序就是最基本的粒子群优化算法程序，用Matlab实现，非常简单。是主函数的源程序，优化函数则以m文件的形式放在Fitness.m里面，对不同的优化函数只要修改Fitness.m就可以了通用性很强。
上传时间： 2013-12-05
上传用户：franktu
小波神经网络的源程序: 1.构造的非线性函数: 位于nninit_test.m 2.直接用WNN逼近非线性:Wnn_test.m, (内部调用小波函数) 3.遗传算法优化后逼近 :GA_Wnn_test.m (内部调用遗传算法的,初始化,适应度,解码函数)-genetic algorithm optimization WNN source : 1. Construction of the nonlinear function : nninit_test.m at 2. WNN directly with nonlinear approximation : Wnn_test.m. (internal called wavelet function) 3. Genetic Algorithm optimization approach : GA_Wnn_test.m (internal called genetic algorithms, initialize, Fitness and decoding functions)
标签： nninit_test GA_Wnn_tes Wnn_test WNN
上传时间： 2016-09-17
上传用户：LIKE
This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY without even the implied warranty of * MERCHANTABILITY or Fitness FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details.
标签： distributed WARRANTY program WITHOUT
上传时间： 2013-12-02
上传用户：star_in_rain
