Situation assessment model for UAV disaster relief in the city

Jia Ren; Xiao Guang Gao

doi:10.1109/M2RSM.2011.5697400

Situation assessment model for UAV disaster relief in the city

Jia Ren
, Xiao Guang Gao

School of Electronics and Information

Northwestern Polytechnical University Xian

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

9 Scopus citations

Abstract

A situation assessment model based on structure-variable discrete dynamic Bayesian network (SVDDBN) of sorting information is proposed for Unmanned Aerial Vehicle (UAV), which can be applied in the condition of disaster relief in the city when pop-up threats appear. The model is built on the basis of the SVDDBN, makes an uncertain classification on popup threats observing information with the help of the posterior probability support vector machine (PPSVM), and finally inputs the classification results into the assessment model as the evidence. For the features of the multi-hidden nodes of the assessment model, the forward algorithm is introduced into the probability inference of the network model, and the inference algorithm of the SVDDBN under the multi-nodes is worked out. The situation that the UAV detects the pop-up threats in the air while conducting the disaster relief in the city is set as the background to verify the correctness of the establishment of the model and the related algorithm.

Original language	English
Title of host publication	2011 International Workshop on Multi-Platform/Multi-Sensor Remote Sensing and Mapping, M2RSM 2011
DOIs	https://doi.org/10.1109/M2RSM.2011.5697400
State	Published - 2011
Event	2011 International Workshop on Multi-Platform/Multi-Sensor Remote Sensing and Mapping, M2RSM 2011 - Xiamen, China Duration: 10 Jan 2011 → 12 Jan 2011

Publication series

Name	2011 International Workshop on Multi-Platform/Multi-Sensor Remote Sensing and Mapping, M2RSM 2011

Conference

Conference	2011 International Workshop on Multi-Platform/Multi-Sensor Remote Sensing and Mapping, M2RSM 2011
Country/Territory	China
City	Xiamen
Period	10/01/11 → 12/01/11

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 11 Sustainable Cities and Communities

Keywords

Posterior probability support vector machine
Situation assessment
Structure-variable discrete dynamic bayesian network
Unmanned aerial vehicle

Access to Document

10.1109/M2RSM.2011.5697400

Cite this

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title = "Situation assessment model for UAV disaster relief in the city",

abstract = "A situation assessment model based on structure-variable discrete dynamic Bayesian network (SVDDBN) of sorting information is proposed for Unmanned Aerial Vehicle (UAV), which can be applied in the condition of disaster relief in the city when pop-up threats appear. The model is built on the basis of the SVDDBN, makes an uncertain classification on popup threats observing information with the help of the posterior probability support vector machine (PPSVM), and finally inputs the classification results into the assessment model as the evidence. For the features of the multi-hidden nodes of the assessment model, the forward algorithm is introduced into the probability inference of the network model, and the inference algorithm of the SVDDBN under the multi-nodes is worked out. The situation that the UAV detects the pop-up threats in the air while conducting the disaster relief in the city is set as the background to verify the correctness of the establishment of the model and the related algorithm.",

keywords = "Posterior probability support vector machine, Situation assessment, Structure-variable discrete dynamic bayesian network, Unmanned aerial vehicle",

author = "Jia Ren and Gao, \{Xiao Guang\}",

year = "2011",

doi = "10.1109/M2RSM.2011.5697400",

language = "英语",

isbn = "9781424494040",

series = "2011 International Workshop on Multi-Platform/Multi-Sensor Remote Sensing and Mapping, M2RSM 2011",

booktitle = "2011 International Workshop on Multi-Platform/Multi-Sensor Remote Sensing and Mapping, M2RSM 2011",

note = "2011 International Workshop on Multi-Platform/Multi-Sensor Remote Sensing and Mapping, M2RSM 2011 ; Conference date: 10-01-2011 Through 12-01-2011",

}

Ren, J & Gao, XG 2011, Situation assessment model for UAV disaster relief in the city. in 2011 International Workshop on Multi-Platform/Multi-Sensor Remote Sensing and Mapping, M2RSM 2011., 5697400, 2011 International Workshop on Multi-Platform/Multi-Sensor Remote Sensing and Mapping, M2RSM 2011, 2011 International Workshop on Multi-Platform/Multi-Sensor Remote Sensing and Mapping, M2RSM 2011, Xiamen, China, 10/01/11. https://doi.org/10.1109/M2RSM.2011.5697400

Situation assessment model for UAV disaster relief in the city. / Ren, Jia; Gao, Xiao Guang.
2011 International Workshop on Multi-Platform/Multi-Sensor Remote Sensing and Mapping, M2RSM 2011. 2011. 5697400 (2011 International Workshop on Multi-Platform/Multi-Sensor Remote Sensing and Mapping, M2RSM 2011).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Ren, Jia

AU - Gao, Xiao Guang

PY - 2011

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N2 - A situation assessment model based on structure-variable discrete dynamic Bayesian network (SVDDBN) of sorting information is proposed for Unmanned Aerial Vehicle (UAV), which can be applied in the condition of disaster relief in the city when pop-up threats appear. The model is built on the basis of the SVDDBN, makes an uncertain classification on popup threats observing information with the help of the posterior probability support vector machine (PPSVM), and finally inputs the classification results into the assessment model as the evidence. For the features of the multi-hidden nodes of the assessment model, the forward algorithm is introduced into the probability inference of the network model, and the inference algorithm of the SVDDBN under the multi-nodes is worked out. The situation that the UAV detects the pop-up threats in the air while conducting the disaster relief in the city is set as the background to verify the correctness of the establishment of the model and the related algorithm.

AB - A situation assessment model based on structure-variable discrete dynamic Bayesian network (SVDDBN) of sorting information is proposed for Unmanned Aerial Vehicle (UAV), which can be applied in the condition of disaster relief in the city when pop-up threats appear. The model is built on the basis of the SVDDBN, makes an uncertain classification on popup threats observing information with the help of the posterior probability support vector machine (PPSVM), and finally inputs the classification results into the assessment model as the evidence. For the features of the multi-hidden nodes of the assessment model, the forward algorithm is introduced into the probability inference of the network model, and the inference algorithm of the SVDDBN under the multi-nodes is worked out. The situation that the UAV detects the pop-up threats in the air while conducting the disaster relief in the city is set as the background to verify the correctness of the establishment of the model and the related algorithm.

KW - Posterior probability support vector machine

KW - Situation assessment

KW - Structure-variable discrete dynamic bayesian network

KW - Unmanned aerial vehicle

UR - https://www.scopus.com/pages/publications/79951740400

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DO - 10.1109/M2RSM.2011.5697400

M3 - 会议稿件

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SN - 9781424494040

T3 - 2011 International Workshop on Multi-Platform/Multi-Sensor Remote Sensing and Mapping, M2RSM 2011

BT - 2011 International Workshop on Multi-Platform/Multi-Sensor Remote Sensing and Mapping, M2RSM 2011

T2 - 2011 International Workshop on Multi-Platform/Multi-Sensor Remote Sensing and Mapping, M2RSM 2011

Y2 - 10 January 2011 through 12 January 2011

ER -

Situation assessment model for UAV disaster relief in the city

Abstract

Publication series

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UN SDGs

Keywords

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