坦克大战非常的完美非常的好玩

说明：  Python编程实现股票自动交易，提供一个测试例子以供参考(Python Programming to Realize Stock Automatic Trading)

针对早期windows系统SMB协议的攻击 前提时先安装安装python 在命令提示符窗口中首先进入py命令所在的文件夹 直接键入python xx.py后回车确认(Attacks on SMB Protocol of Early Windows System Install Python first First enter the folder where the PY command resides in the command prompt window Type Python xx.py directly and return to confirm)

RouteFlow控制器Python代码(SDN RouteFlow Controller)

房价预测系统，利用python语句实现，在读入数据后，利用神经网络训练数据特征，从而实现推荐。(The house price forecasting system is realized by Python statement. After reading the data, the data features are trained by neural network to realize recommendation.)

本书介绍了如何通过Python自动化地完成物理领域方面的研究。全书共分为4个部分，以Python代码为示例向读者介绍了如何用Python解决物理项目中出现的各种问题。(This book describes how to automate research in the field of physics through Python. The book is divided into four parts, with Python code as an example to show readers how to use Python to solve various problems in physical projects.)

说明：  py代码，神经网络和遗传算法的优化预测信息(Optimization prediction information of Py code, neural network and genetic algorithm)

基于scrapyd重写的服务端页面界面.加入了其他一些新功能 如:数据查看,计划任务等 以后准备后续加入: 数据视图,任务分发 多任务发放.

无源传感器网络的分布式能量自适应最小化延迟调度(Distributed Energy Adaptive Minimization Delay Scheduling for Passive Sensor Networks)

直方图去雾算法

说明：  隐马尔科夫模型是关于时序的概率模型，描述由一个隐藏的马尔科夫链随机生成不可观测的状态随机序列，再由各个状态生成一个观测而产生观测序列的过程。隐藏的马尔科夫链随机生成的状态的序列，称为状态序列；每个状态生成一个观测，而由此产生的观测的随机序列，称为观测序列。马尔科夫链由初始概率分布、状态转移概率分布以及观测概率分布确定(The hidden Markov model is a probabilistic model for time series. It describes the process of randomly generating unobservable state random sequences from a hidden Markov chain, and then generating an observation by each state to produce an observation sequence. A sequence of randomly generated states of hidden Markov chains, called a sequence of states; each state produces an observation, and the resulting random sequence of observations is called an observation sequence. Markov chain is determined by initial probability distribution, state transition probability distribution and observation probability distribution)