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Coupling large-scale data flow width learning rapid prediction intelligent algorithm based on network community detection and GCN

A network community and intelligent algorithm technology, applied in neural learning methods, biological neural network models, traffic flow detection, etc.

Inactive Publication Date: 2020-09-22
SOUTHEAST UNIV
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  • Application Information

AI Technical Summary

Problems solved by technology

[0017] The purpose of the present invention is to solve the city-level traffic flow prediction problem, and build a fast prediction intelligent algorithm based on network community detection and GCN coupling large-scale data flow width learning. The technical problem to be solved by the present invention is how to extract the complex features to reduce prediction error and improve prediction speed

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  • Coupling large-scale data flow width learning rapid prediction intelligent algorithm based on network community detection and GCN
  • Coupling large-scale data flow width learning rapid prediction intelligent algorithm based on network community detection and GCN
  • Coupling large-scale data flow width learning rapid prediction intelligent algorithm based on network community detection and GCN

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Embodiment 1

[0082] Embodiment 1: see Figure 1-Figure 5 , a fast prediction intelligent algorithm based on network community detection and GCN coupling large-scale data flow width learning, the algorithm includes the following steps:

[0083] Step 1: Community detection;

[0084] Step 2: Spatio-temporal feature extraction:

[0085] Step 3: Width learning fast prediction;

[0086] Step 4: Large-scale real-time prediction with spatio-temporal coupled width learning neural network.

[0087] The details are as follows: Step 1: Community detection;

[0088] The community detection of the present invention mainly modifies the original FN algorithm, and obtains a new improved FN algorithm including edge weights. Intuitively, modularity represents the normalized value of the difference between the actual number of connected edges in the community and the random expectation of the number of edges generated in the community under the premise of determining the degree of all nodes, so the Q valu...

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Abstract

The invention provides a coupling large-scale data flow width learning rapid prediction intelligent algorithm based on network community detection and GCN. The algorithm comprises the following steps:step 1, community detection; step 2, space-time feature extraction; step 3, width learning rapid prediction; and step 4, large-scale real-time prediction of the space-time coupling width learning neural network. Compared with the prior art, the algorithm has the beneficial effects that intelligent community detection and GCN feature extraction are adopted, width learning is combined, the problemof large-scale node prediction is solved, and the algorithm has the advantages of being high in calculation speed, high in prediction precision, high in adaptive capacity and the like.

Description

technical field [0001] The present invention relates to the fields of complex network technology and machine learning, in particular to an intelligent integrated system composed of hardware equipment with automatic data collection and calculation functions and program software with autonomous community detection and prediction functions. Background technique [0002] In recent years, with the rapid development of technologies such as modern network communication and social media, complex networks have become one of the hot spots of interdisciplinary research. Community detection is an important issue in complex networks, and it is a widely used operation in graph analysis. The goal of the community detection problem is to classify vertices into "communities". The community detection problem differs from the classic graph partitioning problem in that neither the number of communities nor their size distribution is known. Due to the ability to discover structurally coherent v...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G08G1/01G06N3/08G06N3/04
CPCG08G1/0104G08G1/0125G06N3/049G06N3/08G06N3/045
Inventor 虞文武
Owner SOUTHEAST UNIV
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