查询词典 mining

Work in this paper focuses on the data mining from chromatographic retention index data. A retention index database that contains about 50000 records of retention index is firstly established. Projection pursuit technique is then utilized to do data mining upon the data in order to find out some valuable information about the relationship between the retention indices and structural descriptors. A novel algorithm for projection pursuit is developed in this work. Samples of alkane, alkene and cycloalkane are investigated.

中文题名化学数据挖掘新算法和定量构性关系基础研究副题名外文题名 New methodology in chemical data mining and foundational research on QSPR 论文作者杜一平导师梁逸曾学科专业分析化学研究领域\研究方向化学计量学学位级别博士学位授予单位湖南大学学位授予日期2002 论文页码总数115页关键词定量构性关系化学计量学数据挖掘馆藏号BSLW /2003 /O6 /2 化学数据挖掘正逐渐引起化学家们的关注。

In addition, SGID will acquire approximately 10.9 million Quadra Mining shares at a per-share price of CAD 13.91 (US$13.55), in exchange for a 9.9 percent stake in the company.

另外，SGID将以每股13.91加元（13.55美元）的价格收购大约1090万股Quadra Mining股票，从而持有该公司9.9％的股份。

State Grid, China's biggest power utility, has agreed to spend at least US$900m to develop a large copper deposit in Chile in partnership with Vancouver-based Quadra Mining.

中国最大的电力公用事业公司国家电网已同意出资至少9亿美元，与总部位于温哥华的Quadra Mining携手开发智利一个大型铜矿床。

State Grid, China's biggest power utility, has agreed to spend at least US$900m (660m, 599m) to develop a large copper deposit in Chile in partnership with Vancouver-based Quadra Mining.

中国最大的电力公用事业公司国家电网已同意出资至少9亿美元，与总部位于温哥华的Quadra Mining携手开发智利一个大型铜矿床。

And the efficiency and precision of three methods have been analyzed and contrasted by using the CRISP_DM (Cross-industry Process for Data Mining) frame and the step of business understanding, data understanding, data preparation, modeling evaluation and development.

以CRISP_DM(Cross-industry Process for Data Mining)方法论为建模过程框架，按照商业理解、数据准备、建立模型、模型评估、模型发布的步骤，在建模过程中对三种算法的效率和精度进行分析和对比。

From October 16th to 17th, 2006, lead by the subdecanal Hong Xiaowen, the five visitors from Microsoft Research Asia came to visit Nanjing University. On the afternoon of 16th, Doctor Ma Weiying's lecture "Face Recognition and Computer Vision Research at Microsoft Research Asia" was held in room 109 of the technology building in Nanjing University. The room was full of people at that point. On the afternoon of 17th, Doctor Ma Weiying's lecture "Web-scale Data Mining for Search" was held. At the same time, hosted by Gong Yongen, the schoolfellow of Nanjing University and software development engineer in searching technology center of MRA, the experience sharing meeting was held. They won the same nice echo.

2006年10月16日至17日，以洪小文副院长为首的微软亚洲研究院访问团一行5人访问南京大学。10月16日下午，汤晓鸥博士学术报告《Face Recognition and Computer Vision Research at Microsoft Research Asia》在南京大学科技楼109报告厅进行，现场座无虚席。10月17日下午，马维英博士学术讲座《Web-scale Data Mining for Search》以及南京大学校友、微软亚洲研究院搜索技术中心软件开发工程师龚永恩主持的校友经验分享会同时进行，同样取得了热烈的反响。

Eveloped by the Data Mining Group , an independent, vendor led committee, PMML provides an open standard for representing data mining models.

ata Mining Group是一个基金支持的独立的组织，其开发的PMML语言是一种开放的数据模型描述语言。

Partners for this effort include Big Sky Geophysics, Montana Tech, and Stillwater Mining Company.

这方面的合作伙伴包括Big Sky Geophysics，蒙大拿工学院，和 Stillwater Mining 公司。

In a database the concept of an example might change along with time which is known as concept drift When the concept drift the classification model built by use of old data is unsuitable for classify new data Therefore concept drift has become a hot issue in data mining in recent years Although many algorithms had been proposed to resolve this problem they can not provide users with the reason of concept drift However a user might be very interested in such rules For example doctors want to find what makes disease change; researchers want to know the reason of the variety of the weather; and decision makers would like to understand why a customer's shopping habit change In this thesis we propose a Concept Drift Rule mining Tree called CDR-Tree to solve this problem CDR-Tree can not only find the rule of concept drift also build the prediction model for both old and new data at the same time

无论在大型资料库或现实生活中，同一资料样本的概念有可能会随著时间的递移而改变，也就是产生所谓的概念漂移。当样本发生概念漂移时，由旧有资料所建构的分类模组将不再适用於预测新获得的资料，因此，近年来概念漂移已成为资料探勘中一项热门的研究议题。虽然已有？多学者提出不同的技术来解决概念漂移的问题，但是这些方法都是利用修正或重建的方式来产生适合新资料的预测模组，并无法提供造成概念漂移的原因。然而对使用者而言，其感兴趣的可能正是这些引起概念漂移的规则，如医生可能想了解引起疾病变化的主因、学者会想要知道气候转变的规则、或是决策者想找出顾客购物习惯改变的因素等。因此，本论文提出概念漂移规则探勘树( Concept Drift Rule mining Tree )，简称CDR-Tree，来解决这个问题。CDR-Tree不但能探测出造成概念漂移的主要原因，亦能同时建立新旧资料的预测模组以供决策者运用使用。

This text aims at the difference of several representative geology conditions in Yang Shui mining area, carried on the primary election to the mining method of Yang Shui mining area, introduced the new theories of numerical optimization choice of mining method that are fuzzy mathematics and artificial neural network etc, based on the existing mining methods that are feasible, adopt the fuzzy optimization choice principle of flexible neural networks, and synthesize several experts and fieldworkers' opinion, built up the related mathematical model and revised model, carried on processing of programming through computer, thus established each optimization mining project under several representative geology conditions in Yang Shui mining area, and carried on optimizing to the existent unreasonable parameter in mining project;have the great significance to aim at each kind of geology condition for each mining area to adjust the mining method in time in the course of mining, abandon chronically unreasonable mining method, full reclaim the mine's resource, lower the dilution rate、 loss rate of mineral mining, raise the production capacity of stope and economic benefit of mine.

本文针对洋水矿区几种典型地质条件差异，对洋水矿区采矿方法进行了初选，介绍了模糊数学和人工神经网络等采矿方法数值优选新理论，在现有可行性采矿方法的基础上，采用弹性神经网络模糊优选原理，并综合多位专家及现场工作者的意见，建立了相关的数学模型及修正模型，通过计算机进行编程处理，从而确立了洋水矿区几种典型地质条件下各自的最优采矿方案，并针对采矿方案中存在的不合理参数进行了优化，为各矿区针对各类地质条件在采矿过程中及时调整采矿方法，摈弃习惯性的不合理采矿方法，充分回收矿山资源、降低矿石开采的贫化率、损失率，提高采场生产能力以及矿山经济效益具有重大意义。

Graf, without question, is the greatest women's player in history.

格拉芙，现在，毫无疑问是女子网坛历史上最伟大的选手。

If not, you will have to look around at all your important data.

如果没有，您将需要检查所有的重要数据。