Geodesic
Calculation of aircraft area on satellite images by genetic algorithm
Vestnik Ûžno-Uralʹskogo gosudarstvennogo universiteta. Seriâ, Matematičeskoe modelirovanie i programmirovanie, Tome 9 (2016) no. 4, pp. 148-154

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Classical genetic algorithm is used in a computational experiment, which is described in this article, to measure an area of the aircraft Boeing 737-300. Satellite images containing objects of interest are selected as initial data. The computational experiment consists of two steps. The first step presents the generalized formulas of values. These formulas are needed to select initial images, using the theory of modified descriptive algebra of images. After that, the initial data is formed according to the calculated values, i.e. the satellite image is chosen in the needed scale and the shooting angle. At the second step, a model of technical vision system (computer vision system) in the modified descriptive images algebra and a fitness function for the genetic algorithm are developed. Then varying parameters of the model are chosen and their optimization is carried out in MATLAB. The article demonstrates development of the model due to its complexity by additional imaging techniques. Experimentally it was found that the evolution of the model improves optimization results.
Keywords: measurement of an aircraft area; objective function; genetic algorithm; modified descriptive images algebra; combinatorial evaluation of a space; space of image states. 
@article{VYURU_2016_9_4_a13,
     author = {A. R. Iskhakov and R. F. Malikov},
     title = {Calculation of aircraft area on satellite images by genetic algorithm},
     journal = {Vestnik \^U\v{z}no-Uralʹskogo gosudarstvennogo universiteta. Seri\^a, Matemati\v{c}eskoe modelirovanie i programmirovanie},
     pages = {148--154},
     publisher = {mathdoc},
     volume = {9},
     number = {4},
     year = {2016},
     language = {en},
     url = {http://geodesic.mathdoc.fr/item/VYURU_2016_9_4_a13/}
}
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A. R. Iskhakov; R. F. Malikov. Calculation of aircraft area on satellite images by genetic algorithm. Vestnik Ûžno-Uralʹskogo gosudarstvennogo universiteta. Seriâ, Matematičeskoe modelirovanie i programmirovanie, Tome 9 (2016) no. 4, pp. 148-154. http://geodesic.mathdoc.fr/item/VYURU_2016_9_4_a13/