Very good platform for robot soccer matches, a detailed application notes

学习魔方编程技巧，仅供参考，有信息请反馈。-learning programming skills, for reference purposes only, with information feedback. Thank you

此为疾病诊断专家系统，用这种结构建立的知识库可以很方便地实现上面所提到的各种功能。这种结 构的最独特之处就是依靠相同的关键（疾病名或其代码）来实现一种疾病与其症候之 间的相互联系。疾病名与症候分别用二叉树进行排序。排序后可由疾病名而查到与该 疾病名有关的所有详细情况，也可由一种症候而查到哪些疾病有这种症候，以及该症 候可能引起各种疾病的概率。-This is the disease diagnosis expert system, using this structure to establish the knowledge base can easily realize the above mentioned features. The structure of the most unique is that relying on the same key (the disease or its code) to achieve a disease and its symptoms between. Name and symptoms of disease were treated with binary tree sort. Sort by the disease after the name of the disease were found with all the details of which can also be a symptom of the diseases that have found such a symptom, as well as the symptoms may lead to the probability of various diseases.

duda的模式分类作业源代码，第二章上机练习第2题。2类问题的分类器设计。c语言编程。-duda the pattern classification operations source code, the second chapter on the first two aircraft that practice. Two categories of classified design. C programming language.

ID3算法有一定的自学习、自组织能力,适用于复杂系统的智能诊断。以实例验证了该算法对RH-KTB真空抽气系统故障诊断的有效性。-ID3 algorithm to a certain extent self-learning, self-organization, applied to a complex system of intelligent diagnosis. Examples to show that the algorithm of RH- KTB vacuum exhaust system fault diagnosis arrival.

人工智能神经网络识别 人工智能神经网络识别-Artificial neural network artificial neural network to identify

workbench的应用开发-application development workbench

简单规则演化出来的极似苍蝇的一个人工生命群体floy-simple rules of evolution as same flies an artificial life groups floy

通过人工智能算法快速实现神经网络识别，具有更加高效和快速的特点-Through artificial neural network algorithm for rapid identification, have a more efficient and rapid characteristics of

本算法为自适应遗传算法，采用基于排序的选择策略，编码方案为实数编码。能够解决很多优化问题！-The algorithm for the adaptive genetic algorithm, based on the sort of choice strategy, coding schemes for real-coded. Many optimization problems can be solved!

Kohonen网络的学习过程可描述为：对于每一个网络的输入，只调整一部分权值，使权向量更接近或更偏离输入矢量，这一调整过程就是竞争学习。随着不断的学习过程，所有输入矢量都在输入矢量空间相互分离，形成了各自代表输入空间的一类模式，这就是Kohonen网络的特征自动识别的聚类功能。请解压缩后按照readme提示进行操作。-Kohonen network learning process can be described as follows : for each one network input, only part of adjusting the weights, weight vector closer to or further from the input vector, the adjustment process is competitive learning. With the continuous process of learning, all the input vector in the importation of vector space separate form their own representatives importation of a type of space, and this is a Kohonen network of automatic clustering functions. Please decompress after readme according to instructions.