西安电子科技大学模式识别原理与应用课件1

这是一篇关于文本分类问题的综述，详细的介绍了文本分类的技术发展。-text category

改进遗传算法程序-improved genetic algorithm program

基于MATLAB完成的神经网络源程序 大家-Based on the MATLAB neural network to complete the U.S. source

道路识别 人工智能方面的道路识别应用-road artificial intelligence to identify the road recognition applications

用遗传算法求解背包问题是南京航空航天大学信息与计算科学专业编写的.本程序利用遗传算法来求解背包问题.采用二进制字符串编码,1表示选择物体,0则不选择. 背包问题描述:在M件物品取出若干件放在空间为W的背包里，每件物品的重量为W1，W・2……Wn，与之相对应的价值为P1,P2……Pn。求出获得最大价值的方案。注意：在本题中，所有的重量值均为整数。-genetic algorithm knapsack problem is the Nanjing University of Aeronautics and Astronautics, Information and Computing Science prepared. The procedure the use of genetic algorithms to solve knapsack problem. binary string encoding, an option objects, 0 no choice. Knapsack Problem Description : M items removed several pieces on the space-W backpack, Each of the weight W1, W 2 ... Wn, the corresponding value of P1, P2 ... Pn. Sought to gain maximum value of the program. NOTE : In this issue, all the weight values are integers.

利用模拟退火法求解TSP问题 可以求得50个城市的精确解-The use of simulated annealing algorithm for solving TSP problems can be obtained 50 cities Exact Solutions

多步预测,设计简单规范,基于信息建模,具有很强的抗干扰性和鲁棒性.-Multi-step prediction, the design of simple norms, based on information modeling, which has strong anti-jamming and robustness.

停车诱导系统中车位预测模型的研究 摘 要 研究城市停车诱导系统的停车车位占有率预测问题。首先提出墓于B P神经网络的车位占有预测模型， 同时将自适应 学习速率调整法和加入动量项方法用于改善基本B P神经网络， 优化了学习速率， 减少了训练过程的震荡趋势， 改善了网络的收效 隆。以此为基础实现了停车位的智能预测 0最后， 进行了多种方法比对实验-err

This a SVM light for those who want to learn how Support Vector Machine work-This is a SVM light for those who want to learn how Support Vector Machine work

程序演示的是用简单遗传算法随机一个种群，然后根据所给的交叉率，变异率，世代数计算最大适应度所在的代数-Program demonstrates that the simple genetic algorithm with a random population, then according to the crossover rate, mutation rate, calculating the maximum number of generations where the fitness of algebraic