一种运算效率较高的遗传算法

BP人工神经网络算法，用java代码实现，用scilab图像显示，案例是港口吞吐量的预测-BP artificial neural network algorithm, using java code, using scilab image display, case is the throughput of the port prediction

有指导的马尔可夫随机场（MRF）的图像分割代码，是有指导的方式（即用鼠标框出分类样本区域）。采用OpenCV编写。-Has guided Markov Random Field (MRF) image segmentation code, is guiding the way (that is, a classification of the box with the mouse sample region). Prepared using OpenCV.

vb写的改进的遗传算法程序。是一些通用代码，与具体问题对应的代码空出来，用的时候填进去。根据我的经验，要想用好遗传算法，代码必须自己写，因为问题不同，编码，杂交，变异算子可能都不一样。特别是杂交算子，需要根据问题调整，甚至创造出新的杂交方法。而且适应度计算的代码也需要自己写，特别是带约束的优化问题 -vb write improvement in the genetic algorithm. Some common code, with the specific issues the corresponding code space, and the time spent filling into account. According to my experience, in order to make good use of genetic algorithms, code must write their own, because different issues, coding, hybridization and mutation operator may not like. In particular hybrid operator, the need to adjust the problem, or even create a new hybrid method. But fitness calculation of the code required to write their own, especially with the constrained optimization problem

实现了图的搜索算法，包括深度优先搜索，广度优先搜索，Dijstra算法，A*算法等较典型的搜索算法，同时可以进行图的输入和编辑等操作，仅供大家参考。-achieve the plan"s search algorithm, including depth-first search, breadth- first search algorithm Dijstra, A* algorithm is more typical search algorithm, and can map the input and editing operation, only for reference.

本人做的遗传算法源代码，在FORTRAN下打开即可以，可在WINDOUS环境下运行-I do genetic algorithm source code, under the FORTRAN that can be opened, in WINDOUS operating environment

神经网络模拟正弦函数演示-neural network simulation sine function demo

非常简单的一个神经网络小程序 自己写的 还用了遗传算法进行优化-Very simple neural network of a small program written in their own also used genetic algorithms to optimize

这是我写毕业论文的源程序,用模拟退火算法求解VRPTW问题.在我机子上运行过了,结果很好.-This is the thesis I wrote the source code, using simulated annealing algorithm to solve VRPTW problems. In my machine run-off, resulting in very good.

结合均匀设计表和小边经验公式产生初始种群，使TSP应用遗传算法能求出更优更快解，详尽说明见paper.doc。-uniform design combining a small side table and have empirical formula initial population, TSP application of genetic algorithms can be obtained faster and better solutions, detailed description of paper.doc.

clusterfilesrev 最新的分类聚类代码，delphi编写-err