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The dissertation focused on the technologies, algorithm and application of WBSDM, and the main studies and new contributions are described as follows: 1. Technologies of spatial data mining and web-based data mining are summarized and then the concept of WBSDM is put forward and its main functions and meaning of research are disserted in detail. 2. The framework of web-based spatial data mining is presented. And its background, definition, features, functions, system structure, implementation strategy, key technologies and so on are illustrated systematically.

本项研究旨在总结空间数据挖掘技术和基于Web的数据挖掘技术及WBSDM的应用前景;系统地提出基于Web的空间数据挖掘框架;设计基于XML/J2EE的WBSDM平台模型;将MAS(Multi-AgentSystem)技术引入WBSDM并提出应用策略;研究基于粗糙集的空间知识库刻画模型,提出并实现高维数据的特征提取和数据浓缩算法;提出并实现基于知识库的知识发现模型;构造一个WBSDM的原型实验系统,对本文的相关研究进行验证。

The paper summarizes theories and practices concerning data mining at the beginning. According to actual conditions of data forecasting, the paper particularizes two basic tasks in data mining, namely, exploring data analysis and forecasting modeling for classification, and employs them in load forecasting practically. Then a special short-term load-forecasting arithmetic is forwarded based on the former work, which can efficiently take into account weather effects on the load, and hence improve the accuracy of load forecasting.

本文概述了数据挖掘技术的有关内容;并针对负荷预测的实际情况,详细介绍了数据挖掘中的两个基本任务:探索性数据分析和用于分类的预测建模,并将其运用于负荷预测之中;根据所得结果提出了一种基于数据挖掘的短期负荷预测算法,该算法能够有效的考虑气象因素对负荷的影响,从而提高了负荷预测的精度。

Firstly this paper explores the main systerm modeling methods in hydraulic grab;then we focus the analysis on the kinematics and bear of the back shovel dig device, the request of the gig ability, the task efficiency , the endure intension; after that we creat a rational maths model and write a program to ananlysis the data acquired; finally, this paper gets the optimize parameter and scheme, and protracts the grab envelope chart.

论文首先对液压挖掘机主要系统建模方式进行探索,然后重点对反铲挖掘装置运动学及受力进行分析,分析反铲挖掘装置的挖掘能力要求、作业性能要求、作业效率要求、受力状态要求,进行运动学和动力学分析,创建合理的数学模型(设计变量、目标函数的确定),利用合适的优化方法编写计算机程序,调试通过程序应用,最后对优化结果进行分析整理。

The basic concept and general knowledge of data mining were given firstly, and the characteristics and research methods of data mining procedure were explained based on the test-driving database of WS9 aero-engines. Rough set and decision tree, these two classification mining methods were used to extract decision rules, regression analysis was utilized to find the relationship between variables, and the tendency also was predicted.

论文阐述了数据挖掘技术的基本概念和一般知识,分析了基于WS9发动机试车数据库数据挖掘的特点和研究方法,选择了粗糙集和决策树分类挖掘方法提取决策规则,利用回归分析方法发现变量之间的函数关系,并进行趋势预测。

On the one hand, there are lots of association rules theory of application-oriented is waiting for explore and creative in these big theory framework; on the other hand, with the development of data mining and relevance technology, it must will birth new mining theory, and it will have impetus to some particular application, it may merge particular application target, such as marketing, custom relationship managements electronic business.

一方面,在这些大的理论框架下有许多面向实际应用目标的关联规则挖掘理论等待探索和创新;另一方面,随着数据挖掘技术本身和相关技术的发展,新的挖掘理论的诞生是必然的,而且可能对特定的应用产生推动作用,可能融合特定的应用目标,如市场营销、CRM、电子商务等。

Upon this foundation,a corpus-based algorithm was designed and implemented to acquire and filter binary semantic pattern rules automatically. In the algorithm,a data mining method for cross-level association rules is adopted,which is guided by metarule,to find the semantic laws of word combinations in Chinese phrase corpus. Then statistic results are used to filter the findings. In the end,the remains are transformed into binary semantic pattern rules.

在此基础上,本文设计并实现了基于语料库的二元语义模式规则自动挖掘和优选算法,该算法先采用数据挖掘中元规则制导的交叉层关联规则挖掘方法,自动发现汉语短语熟语料库中词语两两组合的语义规律,再根据统计结果自动优选后转换生成候选二元语义模式规则集。

A simple, but typical, process might include prepro- cessing data, applying a data-mining algorithm, and visualizing the mining results.

一个简单、但典型的数据挖掘过程可能包括数据预处理阶段,数据挖掘算法的应用阶段,以及对挖掘结果的可视化处理阶段。

Finally, the thesis defines the steps of implementing data mining, cognizes and summarizes the problems existed, and validates the feasibility that data mining can be used in the customer knowledge management, through a practice of excavation cluster analysis in a case of Grand Hotel client knowledge acquisition.

最后,通过在军山大酒店的客户知识获取应用实例中挖掘聚类分析的实践,明确了在客户知识实施数据挖掘的步骤,认识和总结出实践中出现问题,验证了数据挖掘方法在客户知识管理中运用的可行性。

The Kimberley Diamond Mine holds the title of being the largest hand-dug hole in the world.

金伯利钻石矿坑被认为是世界上最大的人力挖掘矿坑,从1866年至1914年,50000名矿工使用铁铲等工具进行挖掘,共挖掘出2722公斤钻石。

The Kimberley Diamond Mine holds the title of being the largest hand-dug hole in the world. From 1866 to 1914 50,000 miners dug the hole with picks and shovels, yielding 2,722 kg of diamonds.

金伯利钻石矿坑被认为是世界上最大的人力挖掘矿坑,从1866年至1914年,50000名矿工使用铁铲等工具进行挖掘,共挖掘出2722公斤钻石。

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