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System strategy prediction method based on Granger causality and related equipment

A causal relationship, Granger's technology, applied in the field of artificial intelligence, can solve problems such as inaccurate system strategy prediction, and achieve the effect of improving interpretability and model reliability

Pending Publication Date: 2021-12-24
华润数字科技有限公司
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Based on this, aiming at the above-mentioned technical problems, this application provides a Granger causality-based system strategy prediction method, device, computer equipment and storage medium to solve the technical problem of inaccurate system strategy prediction in the prior art

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  • System strategy prediction method based on Granger causality and related equipment
  • System strategy prediction method based on Granger causality and related equipment
  • System strategy prediction method based on Granger causality and related equipment

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Embodiment Construction

[0023] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field of the application; the terms used herein in the description of the application are only to describe specific embodiments The purpose is not to limit the present application; the terms "comprising" and "having" and any variations thereof in the specification and claims of the present application and the description of the above drawings are intended to cover non-exclusive inclusion. The terms "first", "second" and the like in the description and claims of the present application or the above drawings are used to distinguish different objects, rather than to describe a specific order.

[0024] Reference herein to an "embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the present application. The occurrenc...

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Abstract

The embodiment of the invention belongs to the field of artificial intelligence, and relates to a system strategy prediction method based on Granger causality, comprising: collecting related parameters and industrial data, the related parameters comprising at least one module variable of at least one system module, and the industrial data being historical data of each module variable; based on the historical data, performing causal analysis on each module variable by adopting a Granger causal relationship analysis mode based on an attention mechanism to obtain Granger causal strength between the historical data of each module variable and the current data; constructing a graph data structure to describe a system topological structure of the industrial system; and inputting the constructed graph data structure into the prediction model to obtain a prediction result of the system strategy. By adopting the method, the model prediction accuracy is improved.

Description

technical field [0001] The present application relates to the field of artificial intelligence, in particular to a system strategy prediction method, device, computer equipment and storage medium based on Granger causality. Background technique [0002] With the development of computer technology and the application of advanced control systems, the equipment and structure of modern industrial systems are becoming more and more complex, and industrial processes have accumulated a large amount of historical data, which includes the operating rules of the process, operator experience, product quality and process problems. and other rich information. How to obtain useful information from the data and provide a basis for the control and decision-making of the production process when it is difficult to establish an accurate mechanism model has become an issue of widespread concern to researchers and industries. Time series prediction based on industrial data is to use a large amo...

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Application Information

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IPC IPC(8): G06N3/04G06N3/08G06N5/04
CPCG06N3/08G06N5/041G06N3/047G06N3/044G06N3/045Y02P90/30
Inventor 刘雨桐石强熊娇王国勋张兴
Owner 华润数字科技有限公司
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