Research on node network transmission capacity prediction model for large scale remote sensing data collection

Lu Bai, Xiaogang Liu, Man Zhao, Zhibao Wang, Guiying Shi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Abstract

In recent years, the use of remote sensing technology has grown exponentially in various industries such as agriculture, forestry, and urban planning. Remote sensing data collection systems rely on a network of nodes to collect and transmit data. The transmission capacity of these node networks is a critical factor in the performance and efficiency of the entire system. However, accurately predicting the transmission capacity of a node network can be a challenging task. To carry out large scale open remote sensing data collection, it is necessary to predict the network transmission capacity of nodes in the face of the difference in the execution speed of each node for various tasks. It is necessary to predict the network transmission capacity of nodes. In this research, we propose a node network transmission capacity prediction model for large scale remote sensing data collection using a combination of Particle Swarm Optimization (PSO) and Backpropagation (BP) algorithms. The proposed PSO-BP model aims to accurately predict the transmission capacity of a node network in a remote sensing data collection system. The model is tested and evaluated using a large-scale dataset and the results show that the proposed model outperforms existing models in terms of prediction accuracy. This work contributes to the field of remote sensing data collection by providing a reliable and efficient method for predicting the transmission capacity of node networks.

Original languageEnglish
Title of host publicationProceedings of the 39th International Symposium on Remote Sensing of Environment, ISRSE-39
EditorsO. Altan, F. Sunar, D. Klein
PublisherCopernicus Gesellschaft mbH
Pages25-31
Number of pages7
DOIs
Publication statusPublished - 21 Apr 2023
Externally publishedYes
Event39th International Symposium on Remote Sensing of Environment 2023 - Antalya, Turkey
Duration: 24 Apr 202328 Apr 2023

Publication series

NameInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
VolumeXLVIII-M-1-2023
ISSN (Print)1682-1750
ISSN (Electronic)2194-9034

Conference

Conference39th International Symposium on Remote Sensing of Environment 2023
Abbreviated titleISRSE-39
Country/TerritoryTurkey
CityAntalya
Period24/04/202328/04/2023

Keywords

  • BP
  • PSO
  • network transmission capacity
  • prediction model
  • remote sensing data

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