Neuralbase Model for Detection and Recognition of Technological Situations within the Scope of Data Mining Strategy

A. M. Vulfin; A. I. Frid; V. M. Giniyatullin

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Neuralbase Model for Detection and Recognition of Technological Situations within the Scope of Data Mining Strategy

机译：数据挖掘策略范围内用于技术状况检测和识别的神经基础模型

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The article considers the problem of detection and recognition of technological events and oil reception-delivery object states on the base of the analysis of the time-series describing the processes on the object is. Step-by-step, the tasks of preprocessing raw data, segmenting time-series, data clusterization and classification as well as neural net committee building for the object condition diagnosing within the scope of Data Mining strategy are resolved.

机译：本文在描述对象过程的时间序列分析的基础上，考虑了技术事件的检测和识别以及收油对象状态的问题。逐步解决了数据挖掘策略范围内的原始数据预处理，时间序列分割，数据聚类和分类以及用于对象状态诊断的神经网络委员会的任务。

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来源
《Optical memory & neural networks》 |2010年第3期|p.207-212|共6页
作者
A. M. Vulfin; A. I. Frid; V. M. Giniyatullin;
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作者单位

Ufa State Aviation Technical University, K. Marksastr., 12, Ufa, 450000 Russia;

Ufa State Aviation Technical University, K. Marksastr., 12, Ufa, 450000 Russia;

Ufa State Petroleum Technological University, Kosmonavtov St., 1, Ufa, 450062 Russia;

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正文语种 eng
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关键词
detection and recognition; time-series; segmentation; clusterization; classification; neural net committee; data mining strategy;

机译：检测和识别;时间序列;分割;集群;分类;神经网络委员会;数据挖掘策略;

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Neuralbase Model for Detection and Recognition of Technological Situations within the Scope of Data Mining Strategy

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