为有效解决分布式攻击，提出了基于多传感器数据融合与挖掘的分布式入侵检测模型。
To solve the distributed attacks efficiently, this paper presents the Distributed Intrusion Detection Model Based on Multisensor Data Fusion and Mining (DIDM).
提出一种将数据挖掘技术与装配工艺知识相融合的白车身装配尺寸偏差源快速诊断方法。
A rapid diagnosis method synthesized data mining technology and assembly process knowledge for body-in-white assembly dimension error sources is presented.
并通过定义与深入分析故障告警中的关联规则和情节规则，提出了一个基于数据融合和数据挖掘技术的网络故障管理的架构模型。
It presents a new model for network fault management based on data fusion and data mining by defining and discussing the association rule and the frequent episodes.
设计了一种基于粗糙集——模糊神经网络技术的数据挖掘与数据融合集成系统。
One kind of integrated data mining and data fusion system's model is designed with fuzzy neural network based on rough sets.
医学成像新技术、多模态医学成像的图像与信息融合、大数据病例的挖掘，是实现临床精准医疗的重要工程基础。
Precision Medicine relies on advent medical imaging technique, fusion of multi-modality medical imaging and information, and large-scale data mining on medical cases.
将多传感器数据融合与数据挖掘技术应用到分布式入侵检测中，可连续和全面地提供网络攻防战场环境态势的综合评估。
By applying Multisensor Data Fusion and Data Mining to intrusion detection, DIDM provides the comprehensive assessment of network attack and defense situations continuously and globally.
主要研究内容与研究成果如下：◇本文提出了一种通用的数据挖掘结果与模糊专家系统规则库自动融合的模型。
The main researches and contributions are threefold:Propose a general model which could automatically merge newly discovered knowledge with original fuzzy knowledge base.
主要研究内容与研究成果如下：◇本文提出了一种通用的数据挖掘结果与模糊专家系统规则库自动融合的模型。
The main researches and contributions are threefold:Propose a general model which could automatically merge newly discovered knowledge with original fuzzy knowledge base.
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