Optimize TOD placement using genetic algorithm

Namhoon Kim; Hong Gyoo Sohn; Doe Gyu Jeon; Hyo Seon Jang

doi:10.1109/ICCAIS.2014.7020545

Optimize TOD placement using genetic algorithm

Namhoon Kim, Hong Gyoo Sohn, Doe Gyu Jeon, Hyo Seon Jang

Department of Civil and Environmental Engineering

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

Abstract

Geospatial information system (GIS) is widely used in military sides. As an example, penetration analysis is typical for GIS using in military side. In this paper, we apply GIS to analyze the optimized detector location. We use the thermal observation device (TOD), and select Daejeon city to perform this analysis. In this paper, we use DEM data and VITD data. We bring genetic algorithm in our procedure to fine a more effective and global solution. The locations of the rectangular coordinate point (i.e., x and y pixel coordinate) of TOD will be a gene, and a group of TOD locations will be a chromosome. We select the uniform crossover method to make next generation. Target function is composed with detected pixel number part and detection probability part. The research goal of this study is to find the location with the highest target function value. Result of the experiments provide optimized TOD placement.

Original language	English
Title of host publication	2014 International Conference on Control, Automation and Information Sciences, ICCAIS 2014
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	136-139
Number of pages	4
ISBN (Electronic)	9781479972043
DOIs	https://doi.org/10.1109/ICCAIS.2014.7020545
Publication status	Published - 2014 Jan 23
Event	3rd International Conference on Control, Automation and Information Sciences, ICCAIS 2014 - Gwangju, Korea, Republic of Duration: 2014 Dec 2 → 2014 Dec 5

Publication series

Name	2014 International Conference on Control, Automation and Information Sciences, ICCAIS 2014

Other

Other	3rd International Conference on Control, Automation and Information Sciences, ICCAIS 2014
Country	Korea, Republic of
City	Gwangju
Period	14/12/2 → 14/12/5

Bibliographical note

Publisher Copyright:
© 2014 IEEE.

All Science Journal Classification (ASJC) codes

Artificial Intelligence
Information Systems
Control and Systems Engineering

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10.1109/ICCAIS.2014.7020545

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Kim, N., Sohn, H. G., Jeon, D. G., & Jang, H. S. (2014). Optimize TOD placement using genetic algorithm. In 2014 International Conference on Control, Automation and Information Sciences, ICCAIS 2014 (pp. 136-139). [7020545] (2014 International Conference on Control, Automation and Information Sciences, ICCAIS 2014). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCAIS.2014.7020545

Kim, Namhoon ; Sohn, Hong Gyoo ; Jeon, Doe Gyu ; Jang, Hyo Seon. / Optimize TOD placement using genetic algorithm. 2014 International Conference on Control, Automation and Information Sciences, ICCAIS 2014. Institute of Electrical and Electronics Engineers Inc., 2014. pp. 136-139 (2014 International Conference on Control, Automation and Information Sciences, ICCAIS 2014).

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abstract = "Geospatial information system (GIS) is widely used in military sides. As an example, penetration analysis is typical for GIS using in military side. In this paper, we apply GIS to analyze the optimized detector location. We use the thermal observation device (TOD), and select Daejeon city to perform this analysis. In this paper, we use DEM data and VITD data. We bring genetic algorithm in our procedure to fine a more effective and global solution. The locations of the rectangular coordinate point (i.e., x and y pixel coordinate) of TOD will be a gene, and a group of TOD locations will be a chromosome. We select the uniform crossover method to make next generation. Target function is composed with detected pixel number part and detection probability part. The research goal of this study is to find the location with the highest target function value. Result of the experiments provide optimized TOD placement.",

author = "Namhoon Kim and Sohn, {Hong Gyoo} and Jeon, {Doe Gyu} and Jang, {Hyo Seon}",

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doi = "10.1109/ICCAIS.2014.7020545",

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Kim, N, Sohn, HG, Jeon, DG & Jang, HS 2014, Optimize TOD placement using genetic algorithm. in 2014 International Conference on Control, Automation and Information Sciences, ICCAIS 2014., 7020545, 2014 International Conference on Control, Automation and Information Sciences, ICCAIS 2014, Institute of Electrical and Electronics Engineers Inc., pp. 136-139, 3rd International Conference on Control, Automation and Information Sciences, ICCAIS 2014, Gwangju, Korea, Republic of, 14/12/2. https://doi.org/10.1109/ICCAIS.2014.7020545

Optimize TOD placement using genetic algorithm. / Kim, Namhoon; Sohn, Hong Gyoo; Jeon, Doe Gyu; Jang, Hyo Seon.

2014 International Conference on Control, Automation and Information Sciences, ICCAIS 2014. Institute of Electrical and Electronics Engineers Inc., 2014. p. 136-139 7020545 (2014 International Conference on Control, Automation and Information Sciences, ICCAIS 2014).

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

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Kim N, Sohn HG, Jeon DG, Jang HS. Optimize TOD placement using genetic algorithm. In 2014 International Conference on Control, Automation and Information Sciences, ICCAIS 2014. Institute of Electrical and Electronics Engineers Inc. 2014. p. 136-139. 7020545. (2014 International Conference on Control, Automation and Information Sciences, ICCAIS 2014). https://doi.org/10.1109/ICCAIS.2014.7020545

Optimize TOD placement using genetic algorithm

Abstract

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