【作者】 蒋志全；

【导师】 陈燕；

【作者基本信息】 大连海事大学 ， 管理科学与工程， 2004， 硕士

【摘要】 数据挖掘是从大量的、不完全的、有噪声的、模糊的、随机的数据中，提取隐含在其中的、人们事先不知道的、但又是潜在有用的信息和知识的过程。它是一门涉及数据库、人工智能、数理统计、可视化、并行计算等多方面的学科领域的交叉学科。对于一个成熟的数据挖掘应用而言，最重要的是减少为了加入已有的知识而要求用户的干预，从而使数据挖掘的过程更加自动。 “自组织”是指一个系统由内在机制驱动自行从简单向复杂、从粗糙向细致方向发展，不断地提高自身的复杂度和精细度的过程。自组织系统不需要外界的特定干扰，仅依靠系统内部的相互作用来实现空间、时间或功能的结构。 自组织数据挖掘引入自组织的思想，应用数据分组处理方法(Group Method Data Handling，GMDH)，实现数据挖掘过程的自组织控制，并以客观的方式建立一个最优复杂度模型。自组织数据挖掘有效地减少了用户在数据挖掘过程中的干预，使数据挖掘过程更加自动并使建模结果更加客观。 本文系统地阐述了自组织数据挖掘的基本思想、基本模式以及自组织建模的技术——GMDH方法，实现了一个简单高效的推导最优模型的原始输入变量表达式的算法。在国民经济因素分析的应用中，自组织数据挖掘技术自动地创建分析模型并找出国民经济各因素之间的内在关系。在某城市地铁客流量预测的应用中，GMDH方法建立的模型具有很好的预测效果。这些应用证明自组织数据挖掘能在有效地减少用户干预的同时可以建立很好的模型。更多还原

【Abstract】 Data mining is a process of extracting novel and useful knowledge from large amounts of incomplete raw data. Most important for a more sophisticated data mining application is to limit the involvement of users in the general data mining process to the inclusion of existing a priori knowledge while making this process more automated and more objective.Self-organization is a process during which a system, when driven by its own inherent mechanism, develops from roughness to fine and improves its complexity and precision. The spacial, temporal or functional structure of a Self-organizing system forms only through the interaction of the system without any external interference.Self-organizing data mining introduces the self-organizing theory to the data mining process, applying the GMDH (Group Method Data Handling) principle to make the process more automated and more objective. An optimal complex model is created in a self-organizing modeling process and involvement of the users is reduced.This thesis expatiates on the theory of self-organizing data mining, including its main idea, basic pattern, and technology - GMDH Method.Applying the Self-organizing data mining technology, an analysis model is created automatically, which revealing the relation among the factors that influence national economy. A model created by GMDH is effective in the application of forecasting the current quantity of subway passengers.更多还原