不完备数据分析方法的应用研究。
摘要：粗糙集是用来处理不确定、不完备数据的重要工具之一。
Absrtact: Rough set theory is a new mathematical tool to research imprecise and incomplete data.
基于粗糙集理论的不完备数据分析方法，以可辨识矩阵作为算法的基础，提出了一种改进的不完备数据分析方法。
Based on an incomplete data analysis method of the rough set theory and the distinguish matrix, bring forward an improved ROUSTIDA algorithm.
针对这个问题详细阐述了空间不完备数据的检测和填补方法，重点介绍了基于克里格插值法的空间数据填补方法。
The detecting methods and resume methods are particularly introduced in this paper, emphasis on the resuming methods of incomplete spatial data base on kriging interpolation algorithm.
应用粗集理论可以在决策支持系统中对不完备数据进行分析、推理，提取有用特征，简化信息处理，得出肯定结论。
In the Decision Support System the application of Rough Set could analyze, infer to the incomplete data and pick-up useful character, simplify information processing, and get conclusion in the end.
有人怀疑用于判断航班是否禁飞的模型是基于粗略的数据和不完备的科学手段得出的。
Some suspected that the models used to justify the flight ban were based on sketchy data and incomplete science.
气候研究批评家们认为数据不完备，气候模型靠不住，预测不确定。
Critics of climate research argue the data are incomplete, the climate modelling uncertain, the predictions inconclusive.
那么探索一种通用的方法来解决投影数据不完备的情况就显得至关重要。
Therefore, it is essential to explore a new universal method approaching to the incomplete data problems.
为了能够从不完备决策表（IDT）中进行知识发现和数据挖掘，提出一种新的具有对称性的双重可变精度限制容差关系粗集模型（VPLTRST）。
To obtain knowledge and data from incomplete decision table(IDT), the paper presents a new doubly variable precision limited tolerance rough set theory model(VPLTRST).
在进行风险分析和评估过程中，经常遇到样本信息不充分，数据不完备，即小样本问题。
During analyzing and estimating the risk, we often meet with the situation of inadequate sample information and incomplete data, that is, small-sample problem.
粗糙集理论作为一种处理不完备信息的有力工具，已广泛应用于人工智能的许多领域，特别是数据挖掘和知识发现领域。
Rough set theory, a powerful tool to deal with incomplete information, has been widely used in the area of artificial intelligence, especially in data mining and knowledge discovery.
该算法无需改变初始不完备信息系统的结构，能直接处理缺省数据。
The algorithm could deal with incomplete data directly and do not required changing the size of the original incomplete system.
但是，目前仍然有一些问题，如神经网络选定、结构损伤标志量选取、测试数据不完备等，没有得到很好解决。
But there are still some problems to be solved such as selection of neural networks, determination of structural damage indicator and incompletion of measurement.
提出了一种基于粗糙集的不完备信息系统数据填补方法。
This paper brought forward a data packing method of incomplete information system based on rough sets and grey system theory.
本文重点研究了在不完备信息系统中数据动态变化情况下的属性约简问题，针对已有算法提出了改进的算法。
This paper proposed an improved algorithms in incomplete information system data in the context of dynamic changes of attribute reduction for the existing algorithms.
应运而生的技术是数据挖掘，但是传统的挖掘技术对不完备的信息系统表现出了诸多的不足。
The technology arising at the historic moment is data mining, but the traditional technology of data mining demonstrates a great deal of deficiencies to the incomplete information system.
在现实生活中，由于数据的不确定甚至缺损现象的普遍存在，使得数据库使用者面临的信息系统绝大多数都是不完备的。
Because of general phenomena of indefinite data or even imperfect existing, information systems that are presented to user are mostly incomplete.
商空间理论在处理高维、不完备、复杂的、模糊的、海量数据时，有其独特的优势。
Quotient space theory for treatment of high-dimensional, incomplete, complex, vague, massive data, there are unique advantages.
本文简要阐述了数据挖掘的基本原理，针对车辆故障诊断的特殊性和复杂性及诊断中存在的不完备信息和不一致信息，阐述了将粗糙集理论用于车辆故障诊断的必要性。
In this paper the basic theory of data mining is briefly introduced. For particularity and complexity of vehicle faults diagnosis, it is necessary to integrate rough set theory with neural network.
提出了一种基于不完备复模态测量数据修正阻尼陀螺系统有限元模型的有效数值方法。
An efficient numerical method for the finite-element model updating of damped gyroscopic system was developed based on incomplete complex modal measured data.
投影数据不完备可能由设备引起，也可能由于被测物体的自身密度过高致使X射线难以穿透引起。
The incomplete data problems may be caused by many factors, such as, the equipment and the density region of detected objects.
因此研究不完备系统上的数据挖掘具有一定的现实意义。
Therefore, the researches on DM based on incomplete system have certain practical significance.
不完备信息下的数据挖掘是一个难题，但它在实际决策中是不可避免的。
Data mining in incomplete information system is a hard problem but inevitable in uncertain decision.
不完备信息下的数据挖掘是一个难题，但它在实际决策中是不可避免的。
Data mining in incomplete information system is a hard problem but inevitable in uncertain decision.
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