Increase of Energy Engineering Equipment Performance Based on Neural Network Modeling and Cluster Data Analysis

被引：0

作者：

Khoroshev, N. I. ^{[1
]}

Kulikov, M. V. ^{[1
]}

机构：

[1] PNRPU, Microprocessors Means Automat Dept, Perm, Russia

来源：

PROCEEDINGS OF 2017 XX IEEE INTERNATIONAL CONFERENCE ON SOFT COMPUTING AND MEASUREMENTS (SCM) | 2017年

关键词：

data mining; neural networks; adaptive cluster analysis; heat network; boiler units;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

The questions of increase power equipment productivity based on neural network modeling and adaptive cluster analysis are considered. As an research object a boiler units of the heat network of a typical pulp-and-paper industry enterprise, which is a large consumer of steam for technological needs, are considered. The data mining algorithm in the field of power equipment operation, on the basis of which the ranges of the best boiler productivity and steam losses of heat network sections, is offered.

引用

页码：483 / 485

页数：3

共 13 条

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