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A method to improve prediction accuracy by constructing a sample library of typical working conditions of operating data

A technology of operating data and typical working conditions, applied in the intersection of thermal technology and artificial intelligence, can solve problems such as reducing prediction accuracy, processing huge data volumes, and difficult to obtain information on operating conditions of units, ensuring prediction accuracy without affecting The effect of computational efficiency

Inactive Publication Date: 2021-06-04
NORTH CHINA ELECTRIC POWER UNIV (BAODING)
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

It is difficult to obtain all the operating condition information of the unit by randomly selecting data samples, and if all the operating data are used to build a model, a huge amount of data needs to be processed, and it will also bring information redundancy, thereby reducing the prediction accuracy

Method used

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  • A method to improve prediction accuracy by constructing a sample library of typical working conditions of operating data
  • A method to improve prediction accuracy by constructing a sample library of typical working conditions of operating data
  • A method to improve prediction accuracy by constructing a sample library of typical working conditions of operating data

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Embodiment Construction

[0034] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention. On the contrary, the invention covers any alternatives, modifications, equivalent methods and schemes within the spirit and scope of the invention as defined by the claims. Further, in order to make the public have a better understanding of the present invention, some specific details are described in detail in the detailed description of the present invention below. The present invention can be fully understood by those skilled in the art without the description of these detailed parts.

[0035] The present invention will be further described below in conjunction with the accompanying drawings and ...

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Abstract

The invention provides a method for improving prediction accuracy by constructing a sample database of typical working conditions of operating data. The method uses correlation analysis to eliminate redundant variables, uses principal component analysis to perform dimensionality reduction, and aims at the largest working condition information index to search for With a given number of operating data samples, a sample library of typical working conditions is built to cover most of the operating conditions, so as to represent the process characteristics, which will not affect the calculation efficiency and ensure the prediction accuracy of the model when building the model.

Description

technical field [0001] The invention belongs to the cross-technical field of thermal technology and artificial intelligence, and specifically relates to a method for improving prediction accuracy by constructing a sample library of typical working conditions of operating data. Background technique [0002] With the continuous deepening of informatization in the power industry, the amount of data collected by thermal power plants is increasing. The development of technologies such as multiple linear regression, neural networks and support vector machines provides an important theoretical basis for the development and application of data resources. . Using power station operating data to predict and estimate the parameters of the power generation process can provide a model basis for the state monitoring of power station equipment and the safe and optimal operation of units. [0003] When using operating data to build a power generation process parameter model, the prediction...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/04G06Q50/06
CPCG06Q10/04G06Q50/06
Inventor 吕游黄鑫杨婷婷刘吉臻
Owner NORTH CHINA ELECTRIC POWER UNIV (BAODING)