Knowlesys Products

蓝鲸网页数据提取系统是一款强大的信息抓取工具,能够自动准确地从网页中排除广告等无关信息,提取有价值的数据,并整合到指定的关系型数据库中。该系统支持多种类型的网站数据提取,包括半结构化字段数据及电子邮件地址等多种多媒体文件。

Overview   The web is an ocean of information containing more than 10 billion web pages, wherein 90% of them are in non-structured or semi-structured formats. At present, it is expanding with an increasing rate of 1 million pages per day. The information is increasing at an explosive speed while people’s time and energy are limited. The information absolutely valuable for enterprises or individuals is just lying in this worldwide ocean of the Internet, and how to extract them has become one of the most imperative tasks confronting the research institutions that are engaging the important topics of Information Retrieval, Data Mining, Knowledge Management and Competitive Intelligence etc. The Blue Whale Web Data Extraction System(BWDES) is like a huge blue whale who cruises in this information ocean everyday and is capable of automatically and accurately extracting valuable information for you from the webpage ocean wherein a multitudes of useless messages (such as page headers and footers, column listings and advertisement messages) shall be excluded. In more than three year’s time, the Knowlesys Software, Inc. had developed the BWDES – a powerful web information extraction system. It has a stratified structure and a loosely coupled module design comprising many sub-systems. The BWDES can extract designated information in big volume from the web, and integrate them into specified relational databases, thus to help customers to excavate precious stones from the Internet minefield. Since the process converses the information from the semi-structural form into the structural form, from their dispersed state to the concentrated state, and changes them from the remotely existed information to your locally hoarded treasure, as well as from the visual file into the digital record, you can surely extensively use them in the future. The BWDES is capable of doing data extraction from various types of websites. In addition to extracting field data of semi-structured construction, it can also extract some free text information like e-mail addresses and many types of multimedia files. The BWDES is characterized as a stable running, intelligent crawling and accurate extracting software. The BWDES is an information extraction platform. When new extraction task is required, it is necessary to use this platform to configure the new web crawling and extraction script and parameters. A general database access layer is developed in the BWDES that enables its back end connect to any relational database, such as MS SQL Server, Oracle, DB2, Sybase, MySQL and InterBase etc, even those file database like the Access database. Regardless which type the database is, the extracted data can be checked with a general database browser, as well as export them into various formats such as XML, CVS, HTML, Excel and so on.   Where it is used   Acquiring key information: Obtain all kinds of professional database Competitive information system: Monitor through key words the marketing information of your adversaries who compete with you on the Internet media. Enterprise content management: Accurately acquire outside content in batches and dispose them automatically. Database marketing: Extract comment and contact messages of potential customers from message books, forums and newsgroups. Comparison system: The commodity pricing comparison system. Enterprise Integration Portal: Embed real-time contents of external websites into your EIP interface. Integration of Internet information: Put together the information extracted from the same category websites such as personal resume, employment message, lease and rent message, commodity message and company directory etc. Personal information agent: Integration of up-to-date information from various websites in which individuals or enterprises might be interested, and provide them to users through E-mail or just pasting them on your webpages, thus to save the time iof browsing and downloading.

 

For more information, please visit our website: http://www.knowlesys.com

【故障诊断】【pytorch】基于CNN-LSTM故障分类的轴承故障诊断研究[西储大学数据](Python代码实现)内容概要:本文介绍了基于CNN-LSTM神经网络模型的轴承故障分类方法,利用PyTorch框架实现,采用西储大学(Case Western Reserve University)公开的轴承故障数据集进行实验验证。该方法结合卷积神经网络(CNN)强大的特征提取能力和长短期记忆网络(LSTM)对时序数据的建模优势,实现对轴承不同故障类型和严重程度的高精度分类。文中详细阐述了数据预处理、模型构建、训练流程及结果分析过程,并提供了完整的Python代码实现,属于典型的工业设备故障诊断领域深度学习应用研究。; 适合人群:具备Python编程基础和深度学习基础知识的高校学生、科研人员及工业界从事设备状态监测与故障诊断的工程师,尤其适合正在开展相关课题研究或希望复现EI级别论文成果的研究者。; 使用场景及目标:① 学习如何使用PyTorch搭建CNN-LSTM混合模型进行时间序列分类;② 掌握轴承振动信号的预处理与特征学习方法;③ 复现并改进基于公开数据集的故障诊断模型,用于学术论文撰写或实际工业场景验证; 阅读建议:建议读者结合提供的代码逐行理解模型实现细节,重点关注数据加载、滑动窗口处理、网络结构设计及训练策略部分,鼓励在原有基础上尝试不同的网络结构或优化算法以提升分类性能。
评论
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