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Dynamic intuitionistic fuzzy cognitive map construction method, time sequence prediction method and time sequence prediction system.

A fuzzy intuition and time series technology, applied in neural architecture, character and pattern recognition, biological neural network models, etc., can solve problems such as the complexity of time series and the inability to determine the trend of model data changes, so as to improve the efficiency and accuracy of prediction , avoid subjective influence, and the model predicts accurate results

Inactive Publication Date: 2019-08-02
SHANDONG NORMAL UNIV
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Problems solved by technology

[0006] The inventor also found that by introducing intuitionistic fuzzy sets to construct the intuitionistic fuzzy cognitive map, the intuitional fuzzy cognitive map used for medical decision-making and prediction in the past was constructed according to the experience and known knowledge of experts. Will change again, but due to the complexity and variability of time series, it is impossible to determine whether the constructed model meets the next data trend

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  • Dynamic intuitionistic fuzzy cognitive map construction method, time sequence prediction method and time sequence prediction system.
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  • Dynamic intuitionistic fuzzy cognitive map construction method, time sequence prediction method and time sequence prediction system.

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[0096] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0097] 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.

[0098] 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 combinatio...

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Abstract

The invention provides a dynamic intuitionistic fuzzy cognitive map construction method, a time sequence prediction method and a time sequence prediction system. The dynamic intuitionistic fuzzy cognitive map construction method comprises the following steps: clustering standardized time sequence data into nodes of an intuitionistic fuzzy cognitive map by utilizing fuzzy C-means clustering; training a weight matrix of the intuitionistic fuzzy cognitive map to obtain an initial intuitionistic fuzzy cognitive map; receiving new standardized time sequence data and inputting the new standardized time sequence data into the initial intuitionistic fuzzy cognitive map; adjusting the position of a clustering center of the intuitionistic fuzzy cognitive map by utilizing dynamic fuzzy C-means clustering to obtain a dynamic intuitionistic fuzzy cognitive map; in the process of adjusting the position of the cluster center of the intuitionistic fuzzy cognitive map, judging whether the data at the current moment has concept drift or not by utilizing drift detection if the data at the current moment successfully fall into an existing cluster and an error between a real value solved by utilizing the adjusted intuitionistic fuzzy cognitive map and a predicted value is greater than a preset error threshold value and if so, adjusting a weight matrix of the intuitionistic fuzzy cognitive map; otherwise, not changing the intuitionistic fuzzy cognitive map.

Description

technical field [0001] The disclosure belongs to the field of time series forecasting, and in particular relates to a method for constructing a dynamic intuitionistic fuzzy cognitive map, a time series forecasting method and a system. Background technique [0002] The statements in this section merely provide background information related to the present disclosure and do not necessarily constitute prior art. [0003] Fuzzy Cognitive Map (FCM) is represented by a graph structure, which is composed of nodes and arcs. Nodes can be concepts, entities, etc., and arcs represent the causal relationship between concepts or entities. It is fundamentally different from traditional intelligent computing methods, and it can conveniently use matrix to represent and reason about knowledge. Because it is the product of the combination of fuzzy logic and neural network, it can be regarded as an object-oriented single-layer neural network with feedback from the structural point of view, so...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/04G06K9/62
CPCG06N3/043G06F18/23213
Inventor 骆超王媛
Owner SHANDONG NORMAL UNIV
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