Metallurgy enterprise gas flow interval predicting method based on Bootstrap echo state network integration

A technology of echo state network and prediction method, applied in the field of information to achieve the effect of ensuring completeness

Inactive Publication Date: 2015-03-11
DALIAN UNIV OF TECH
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Problems solved by technology

[0005] The technical problem to be solved by the present invention is the prediction problem of gas flow interval in existing metallurgical enterprises

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  • Metallurgy enterprise gas flow interval predicting method based on Bootstrap echo state network integration
  • Metallurgy enterprise gas flow interval predicting method based on Bootstrap echo state network integration
  • Metallurgy enterprise gas flow interval predicting method based on Bootstrap echo state network integration

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Embodiment Construction

[0024]In order to better understand the technical scheme of the present invention, the embodiment of the present invention will be described in detail below in conjunction with specific cases. Accompanying drawing 2 is the gas flow monitoring curve of a certain domestic metallurgical enterprise, wherein 2 (a) is the flow rate of 3# blast furnace gas The graph, Fig. 2(b) is the converter gas flow graph for the 2# blast furnace. Although on-site gas dispatchers use manual real-time monitoring and empirical methods to predict changes in gas flow in the future, due to the large number of users in the gas system, estimating the changes in the flow of each user in the gas system in the future requires a lot of work. Personnel lack the necessary analysis on the reliability of the estimated results, which will increase the risk of scheduling. Therefore, it is necessary to establish a reasonable gas system flow prediction model, and be able to effectively evaluate the reliability of th...

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Abstract

The invention belongs to the technical field of information, relates to a resampling method, a Bootstrap estimation and Bayesian estimation method and an echo state network integration theory, and specifically relates to a metallurgy enterprise gas flow interval predicting method based on Bootstrap echo state network integration. The method comprises the steps of firstly, performing re-sampling processing on the flow data of each user of a gas system to construct an effective training sample by use of the existing historical data of a metallurgy enterprise site, secondly, establishing an interval prediction model based on the echo state network integration and predicting the gas system user flow within specified time length after a current time point, and finally, estimating the influence of the uncertainty of the model and the data on the prediction result based on the Bootstrap method and the Bayesian method, respectively, thereby constructing a confidence interval and a prediction interval. The metallurgy enterprise gas flow interval predicting method based on Bootstrap echo state network integration can be widely applied to other energy medium systems of the metallurgy enterprises.

Description

technical field [0001] The invention belongs to the field of information technology, relates to a resampling method, a Bootstrap estimation method, a Bayesian estimation method and an echo state network integration theory, and is a gas flow interval prediction method for metallurgical enterprises based on the Bootstrap echo state network integration. The present invention utilizes the existing historical data at the metallurgical enterprise site, first re-samples the flow data of each user in the gas system to construct an effective training sample; then establishes an interval prediction model based on echo state network integration, and predicts the specified time after the current time point The gas system user flow within the length; finally, based on the Bootstrap method and the Bayesian method to estimate the impact of model and data uncertainty on the prediction results, and then construct the confidence interval and prediction interval. This method can be widely used i...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/00
Inventor 赵珺盛春阳刘颖王伟
Owner DALIAN UNIV OF TECH
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