FGn and Poisson process-based power Internet of Things flow prediction method
The invention relates to an FGn and Poisson process-based power Internet of Things traffic prediction method, which comprises the following steps of: carrying out data classification on power Internet of Things access nodes, and establishing a plurality of traffic characteristic data storage librari...
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| creator | CHEN DUANYUN ZHENG JUNRONG LIU ZUFENG LI YUANJIU LIN ZHIHANG ZHANG HONGPO WU GUANXIONG CHEN SHIMING YAN SIHAI XIE YONGTIAN |
| description | The invention relates to an FGn and Poisson process-based power Internet of Things traffic prediction method, which comprises the following steps of: carrying out data classification on power Internet of Things access nodes, and establishing a plurality of traffic characteristic data storage libraries according to the classification; collecting data according to the classification of each flow characteristic database; effective data in a specific time node being selected, data preprocessing and feature extraction being carried out, and data features being obtained; establishing a preliminary flow prediction model according to the data features, and constructing a fractional order Gaussian noise model and a Poisson distribution data model; the fractional order Gaussian noise model and the Poisson distribution data model being merged into the initial flow prediction model for denoising, and a single-time-node prediction model being formed; and repeating the steps to generate prediction models of single time nod |
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| subjects | ELECTRIC COMMUNICATION TECHNIQUE ELECTRICITY INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS PHYSICS TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHICCOMMUNICATION |
| title | FGn and Poisson process-based power Internet of Things flow prediction method |
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