Now take a look at the the reverse process — building an in-memory object model from a data stream.
现在看看相反的过程，从数据流建立内存对象模型。
After carefully studying the common characteristic of varied applications on storing streaming data to the database, a stream storage model was proposed.
通过仔细研究存储流数据的各种应用的共同特征，提出了一种数据流存储模型。
Translate the CWS (or other clinical database) relational database into an XML stream and re-constitute the data in a better normalized data model.
将CWS（或者其他的临床资料库）相关资料库转化成一个XML流，并且重建一个较好的规范化资料模型上的数据。
A mathematical model that characterizes the affects of the updating cycle of sliding window and data stream rate on predictive accuracy is also presented.
还提出了滑动窗口的更新周期、数据流的流速对预测精度影响的数学模型。
First, the piecewise fractal model on data stream is introduced, and then based on this model the algorithm for detecting bursts is presented.
首先给出了数据流上的分段分形模型，进而基于该模型设计了突变检测算法。
In addition, the data stream parsing, extraction protocol characteristics, the establishment of ATM, IP protocol type algorithm model for rapid identification.
另外，对数据流进行解析，提取协议特征，建立A TM、IP协议类型快速识别算法模型。
This paper presents a forecasting model of runoff to Wuyandong subterranean stream system by BP ANN based on the data of precipitation and flux in Luota, west Hunan.
采用湖南洛塔地区屋檐洞地下河系统降水—径流资料训练BP人工神经网络，建立了该系统的径流预测模型。
Finally the problems in applying the MADSPM model to association rule mining in stream data are discussed and the strategies for solving them are also given.
最后对基于MADSPM模型的流数据关联规则挖掘问题中需注意的一些问题进行了阐述与分析。
Based on seismic lines, hydrocarbon source rock, lithology, thermal stream and test data, a two dimensional forward model of the basin has been made.
以地震主测线为格架，结合烃源岩、岩性、热流、测试分析资料为依据，采用正演法开展二维盆地模拟工作。
This paper describes the relevant concepts and presents a model of CBR based on dynamic data stream mining, and gives an improved clustering algorithm of data stream.
首先阐述了相关概念，接着提出了一种基于动态数据流挖掘的案例推理模型，其中动态数据流挖掘算法采用改进的数据流聚类算法。
In Stream Model of Industry, The application of Data Mining must bring higher product yield and quality, and create more benefit.
在流程型工业中，数据挖掘的应用必定会给工业带来更高的产品产量与质量，以及创造更大的效益。
Secondly, the anomaly detection model based on K-means algorithm and SOM network is constructed. It can classify the normal and abnormal network data stream so better to detect the unknown attack.
提出了一种k-均值聚类算法和SOM自组织神经网络算法相结合的异常检测模型，使得系统可以更好的分类正常数据流和异常数据流，以此来防范未知的攻击。
Secondly, the anomaly detection model based on K-means algorithm and SOM network is constructed. It can classify the normal and abnormal network data stream so better to detect the unknown attack.
提出了一种k-均值聚类算法和SOM自组织神经网络算法相结合的异常检测模型，使得系统可以更好的分类正常数据流和异常数据流，以此来防范未知的攻击。
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