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:: Volume 1, Issue 2 (3-2014) ::
jgit 2014, 1(2): 15-32 Back to browse issues page
Optimal Spatial Distribution of Sources of Electromagnetic Wave Propagation for Acquiring Best Qualitative Coverage (Using Genetic Algorithms in GIS)
Ebrahim Omidi Garakani * , Ali Mansourian , Mohammad Saadi Mesgari , Ehsan Omidi Garakani
K.N.Toosi University of Technology
Abstract:   (5535 Views)
Optimal multiple viewpoints problem (OMVP) is an optimization problem, which could not be solved by using analytical methods, since there is not any distinct mathematical relationship between the positions of viewpoints and combinatorial viewshed. Due to the variety of applications of OMVP in communications, surveying, military, urban planning, etc., it is necessary to find a solution. Current solutions include many shortcoming, and disadvantages such as: “not considering the quality of coverage (quality of the received signal)” and “not being applicable because of high number of calculations”. In this paper, a new genetic method has been used to solve OMVP which resolves the mentioned shortcomings, considerably. In this method, each viewpoint is considered as a gene and each N viewpoint compose a chromosome. The quality problem is solved by considering electromagnetic wave attenuation model as the fitness function. The number of calculations has also been considerably reduced by integrated utilization of DEM and TIN, Were TIN vertices are used as the first genes instead of DEM pixels. The results of the practical test showed the flexibility and applicability of the proposed method for OMVP.
Keywords: Viewshed, Wave propagation model, Optimal multiple viewpoints problem (OMVP), Wave attenuation, Genetic algorithm, Optimization, TIN
Full-Text [PDF 2055 kb]   (2387 Downloads)    
Type of Study: Research |
Received: 2015/02/19 | Accepted: 2015/02/19 | Published: 2015/02/19
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Omidi Garakani E, Mansourian A, Mesgari M S, Omidi Garakani E. Optimal Spatial Distribution of Sources of Electromagnetic Wave Propagation for Acquiring Best Qualitative Coverage (Using Genetic Algorithms in GIS). jgit 2014; 1 (2) :15-32
URL: http://jgit.kntu.ac.ir/article-1-61-en.html

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Volume 1, Issue 2 (3-2014) Back to browse issues page
نشریه علمی-پژوهشی مهندسی فناوری اطلاعات مکانی Engineering Journal of Geospatial Information Technology
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