Code Search Engine Krugle Announces Partnership With Amazon

Krugle与亚马逊合作

Code Search Engine Krugle Announces Partnership With Amazon Written by Josh Catone / October 17, 2007 8:37 AM / 1 Comments « Prior Post Next Post » Krugle, the eponymous code search engine launched by Ken Krugler in June 2006, is announcing today a partnership with Amazon to provide enterprise code search for Amazon's Web Services developer network. Krugle has recently announced similar alliances with IBM developerWorks, Collab.net, SourceForge.net, and Yahoo! Developer Network. Krugle's search engine now searches 2.5 billion lines of code -- up from 1 billion at launch just over a year ago -- and reaches one third of all developers world wide, according to the company. The Krugle DevNetwork Edition being deployed for Amazon will allow developers to search for AWS code examples and other resources across Amazon's sites and outside resource sites defined by the company from a single location. "Search is driving significant changes in software development," said Steve Larsen, CEO and co-founder, Krugle on the need for code search. "Developers are looking for ways to get their work done faster, allowing them to spend less time finding code and more time doing interesting and innovative development." Krugle calls this method "search driven development." The site has built parsers for 42 different languages, allowing it, for example, to tell the difference between functions and classes -- more than I can say personally! Krugle delivers related results culled from places like forums, white papers, API documentation, blog posts, and other related projects alongside its code search results. Krugle thinks that their search driven development idea is essential for software developers in the future. More and more free, reusable code and development information is being put online, but there is so much of it that it becomes overwhelming for developers to wade through. When Krugle announced its search partnership with SourceForge.net in April, the site hosted 145,000 projects, for example. Today, just a few months later, that number has grown to around 160,000 projects. Before Krugle's code search was available on the site, finding relevant code meant downloading projects and slogging through them by hand -- now developers can search before they have to download anything. Krugle appears to be beating its chief rivals in the code search vertical, such as Google. Though I have no hard numbers to back that assertion up, anecdotal evidence like the sheer number of LOCs indexed and the partnerships that Krugle is entering into with major enterprise code repositories like those run by Amazon, Yahoo! and IBM would suggest that their technology is performing well against or even outperforming rivals. For more information on Krugle, check out this post at AltSearchEngines from last month.

提供了基于BP(Back Propagation)神经网络结合PID(比例-积分-微分)控制策略的Simulink仿真模型。该模型旨在实现对杨艺所著论文《基于S函数的BP神经网络PID控制器及Simulink仿真》中的理论进行实践验证。在Matlab 2016b环境下开发,经过测试,确保能够正常运行,适合学习和研究神经网络在控制系统中的应用。 特点 集成BP神经网络:模型中集成了BP神经网络用于提升PID控制器的性能,使之能更好地适应复杂控制环境。 PID控制优化:利用神经网络的自学习能力,对传统的PID控制算法进行了智能调整,提高控制精度和稳定性。 S函数应用:展示了如何在Simulink中通过S函数嵌入MATLAB代码,实现BP神经网络的定制化逻辑。 兼容性说明:虽然开发于Matlab 2016b,但理论上兼容后续版本,可能会需要调整少量配置以适配不同版本的Matlab。 使用指南 环境要求:确保你的电脑上安装有Matlab 2016b或更高版本。 模型加载: 下载本仓库到本地。 在Matlab中打开.slx文件。 运行仿真: 调整模型参数前,请先熟悉各模块功能和输入输出设置。 运行整个模型,观察控制效果。 参数调整: 用户可以自由调节神经网络的层数、节点数以及PID控制器的参数,探索不同的控制性能。 学习和修改: 通过阅读模型中的注释和查阅相关文献,加深对BP神经网络与PID控制结合的理解。 如需修改S函数内的MATLAB代码,建议有一定的MATLAB编程基础。
评论
成就一亿技术人!
拼手气红包6.0元
还能输入1000个字符
 
红包 添加红包
表情包 插入表情
 条评论被折叠 查看
添加红包

请填写红包祝福语或标题

红包个数最小为10个

红包金额最低5元

当前余额3.43前往充值 >
需支付:10.00
成就一亿技术人!
领取后你会自动成为博主和红包主的粉丝 规则
hope_wisdom
发出的红包
实付
使用余额支付
点击重新获取
扫码支付
钱包余额 0

抵扣说明:

1.余额是钱包充值的虚拟货币,按照1:1的比例进行支付金额的抵扣。
2.余额无法直接购买下载,可以购买VIP、付费专栏及课程。

余额充值