On-line sequence data prediction method and device

A sequence data and prediction method technology, applied in the field of online sequence data prediction methods and devices, can solve the problems of not considering the internal correlation of sequence data, affecting the accuracy of sequence data prediction, etc., and achieve the effect of improving accuracy

Inactive Publication Date: 2018-11-27
SHANDONG NORMAL UNIV
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Problems solved by technology

Therefore, the existing fuzzy system does not consider the internal correlation of sequence data, which affects the accuracy of sequence data prediction

Method used

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  • On-line sequence data prediction method and device
  • On-line sequence data prediction method and device
  • On-line sequence data prediction method and device

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[0064] It should be pointed out that the following detailed description is exemplary and intended to provide further explanation to the present application. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0065] It should be noted that the terminology used here is only for describing specific implementations, and is not intended to limit the exemplary implementations according to the present application. As used herein, unless the context clearly dictates otherwise, the singular is intended to include the plural, and it should also be understood that when the terms "comprising" and / or "comprising" are used in this specification, they mean There are features, steps, operations, means, components and / or combinations thereof.

[0066] Explanation of terms:

[0067] MF: membership function, membership function;

[0068] NMF: non-membersh...

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Abstract

The invention discloses an on-line sequence data prediction method and device. The prediction method includes: constructing an interval type-2 intuitionistic loop fuzzy neural network model; and training the interval type-2 intuitionistic loop fuzzy neural network model. The special procedure is as follows: recursively updating an average and an standard deviation to standardize sequence data samples; selecting an intuitionistic fuzzy set fuzzy rule on the basis of a dynamic clustering method of recursive computation of an approximate density center; inputting the standardized sequence data samples into the interval type-2 intuitionistic loop fuzzy neural network model with the selected intuitionistic fuzzy set fuzzy rule, outputting a sequence data prediction result, and determining whether the sequence data prediction result meets a preset precision requirement or not; completing training of the interval type-2 intuitionistic loop fuzzy neural network model; otherwise, updating an output weight, a feedback weight, an intuitionistic fuzzy set fuzzy rule center and a point difference until the output prediction result reaches the preset accuracy requirement; and inputting on-line sequence data into the trained model to obtain a prediction result.

Description

technical field [0001] The invention belongs to the field of sequence data processing, and in particular relates to an online sequence data prediction method and device. Background technique [0002] At present, sensor data streams and user behavior data have become the main data sources on the Internet of Things and mobile Internet today, and these data are mainly presented in a sequential manner. The meanings of behavioral data collected in different mobile applications are also different, which can be the user's geographic location coordinates, check-in records, mobile phone program usage records, etc. These data are constantly updated over time. [0003] Traditional algorithms related to sequence data processing are based on fixed system architecture, in which the network structure cannot be adaptively updated with the reasoning process. For sequential data (such as time series), due to concept drift and the existence of breakpoints, static inference structures and fix...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/04
CPCG06N3/043
Inventor 骆超
Owner SHANDONG NORMAL UNIV
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