Making inferences about settlements from satellite images using glowworm swarm optimization
| dc.contributor.author | Avuçlu, Emre | |
| dc.contributor.author | Elen, Abdullah | |
| dc.contributor.author | Kahramanlı Örnek, Humar | |
| dc.date.accessioned | 2021-02-04T07:46:05Z | |
| dc.date.available | 2021-02-04T07:46:05Z | |
| dc.date.issued | 2020 | |
| dc.department | Teknik Bilimler Meslek Yüksekokulu | |
| dc.description | Avuçlu, Emre ( Aksaray, Yazar ) | |
| dc.description.abstract | Optimization is the process of choosing the best one among existing possibilities under particular circumstances in a problem. There are various algorithms for optimization problems nowadays. Metaheuristic algorithms are the algorithms giving almost optimum solutions at an acceptable duration for the problems of large dimension. Heuristic optimization algorithms with general aim are evaluated in different groups. Swarm intelligence-based optimization algorithms were developed through examining the behaviors and movements of living flocks such as birds, fish, cats, and bees. With these algorithms, some estimating processes are carried out successfully in all areas. In this study a new approach was presented with a novel idea, by inspiring from the behavior type of Glowworm Swarm Optimization; and an application estimating the total population, square measurement and electricity quantity that was consumed by the chosen areas in a region was developed. The developed application works as a real-time and animated display. When all calculations are finished, the animation ends. Estimates also examined England as an example. The difference between the estimated value of the actual population of England is calculated as 1.7%. In the estimates for the values of the surface area of England with an error of 1.4%, the estimated values were very close to the actual values. Some other obtained estimation results are presented in the results section. | |
| dc.identifier.doi | 10.1007/s42835-020-00509-3 | |
| dc.identifier.endpage | 2360 | en_US |
| dc.identifier.issn | 1975-0102 | |
| dc.identifier.issue | 5 | en_US |
| dc.identifier.scopusquality | Q2 | |
| dc.identifier.startpage | 2345 | en_US |
| dc.identifier.uri | https:/dx.doi.org/10.1007/s42835-020-00509-3 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12451/7723 | |
| dc.identifier.volume | 15 | en_US |
| dc.identifier.wos | WOS:000561892400002 | |
| dc.identifier.wosquality | Q4 | |
| dc.indekslendigikaynak | Web of Science | |
| dc.indekslendigikaynak | Scopus | |
| dc.language.iso | en | |
| dc.publisher | Korean Institute of Electrical Engineers | |
| dc.relation.ispartof | Journal of Electrical Engineering and Technology | |
| dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | |
| dc.rights | info:eu-repo/semantics/openAccess | |
| dc.subject | Glowworm Swarm Optimization | |
| dc.subject | Heuristics | |
| dc.subject | Satellite Images | |
| dc.subject | Simulation | |
| dc.title | Making inferences about settlements from satellite images using glowworm swarm optimization | |
| dc.type | Article |
