Application of Improved Electromagnetism-like Mechanism Algorithm on Massive Remote Sensing Image Screening
In recent years, remote sensing data have gradually shown a trend towards big data. The cost of the efficient storage, transmission, and processing of multi-source massive remote sensing data is very high. In practical applications, it is usually necessary to screen out data that meet specific cover...
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MDPI AG
2025-03-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/15/7/3542 |
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| author | Yingjie Fang Kun Liu Xun Zhang Gang Lin Huibing Wang Lina Dong Su Li |
| author_facet | Yingjie Fang Kun Liu Xun Zhang Gang Lin Huibing Wang Lina Dong Su Li |
| author_sort | Yingjie Fang |
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| description | In recent years, remote sensing data have gradually shown a trend towards big data. The cost of the efficient storage, transmission, and processing of multi-source massive remote sensing data is very high. In practical applications, it is usually necessary to screen out data that meet specific coverage requirements from a large amount of remote sensing data, which can be regarded as a set covering problem. The traditional manual screening method is time-consuming and labor-intensive, making it difficult to meet the needs of large-scale information processing and analysis tasks across multiple fields. To improve the screening efficiency, people usually adopt the greedy algorithm for data screening, which may lead to becoming trapped in a local optimal solution. In this paper, an improved electromagnetism-like mechanism algorithm is proposed to solve the optimal screening problem of remote sensing data, using the tent chaotic map to construct the initial population, combining with a new local search strategy, and introducing the idea of differential evolutionary algorithm. The experimental results show that the improved algorithm has significant advantages in the optimal screening problem of massive remote sensing data. Compared with the greedy algorithm, the optimal solution of the improved algorithm is increased by about 9.78% on average. Compared with the original algorithm, it can search for the global optimal solution more quickly and has better robustness. |
| format | Article |
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| institution | OA Journals |
| issn | 2076-3417 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | MDPI AG |
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| series | Applied Sciences |
| spelling | doaj-art-4b0e8b7ea80f4c84bd89098e4e48eace2025-08-20T02:15:55ZengMDPI AGApplied Sciences2076-34172025-03-01157354210.3390/app15073542Application of Improved Electromagnetism-like Mechanism Algorithm on Massive Remote Sensing Image ScreeningYingjie Fang0Kun Liu1Xun Zhang2Gang Lin3Huibing Wang4Lina Dong5Su Li6College of Computer and Artificial Intelligence, Beijing Technology and Business University, Beijing 100048, ChinaLand Satellite Remote Sensing Application Center, Ministry of Natural Resources of the People’s Republic of China, Beijing 100048, ChinaCollege of Computer and Artificial Intelligence, Beijing Technology and Business University, Beijing 100048, ChinaInstitute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, ChinaLand Satellite Remote Sensing Application Center, Ministry of Natural Resources of the People’s Republic of China, Beijing 100048, ChinaLand Satellite Remote Sensing Application Center, Ministry of Natural Resources of the People’s Republic of China, Beijing 100048, ChinaCollege of Computer and Artificial Intelligence, Beijing Technology and Business University, Beijing 100048, ChinaIn recent years, remote sensing data have gradually shown a trend towards big data. The cost of the efficient storage, transmission, and processing of multi-source massive remote sensing data is very high. In practical applications, it is usually necessary to screen out data that meet specific coverage requirements from a large amount of remote sensing data, which can be regarded as a set covering problem. The traditional manual screening method is time-consuming and labor-intensive, making it difficult to meet the needs of large-scale information processing and analysis tasks across multiple fields. To improve the screening efficiency, people usually adopt the greedy algorithm for data screening, which may lead to becoming trapped in a local optimal solution. In this paper, an improved electromagnetism-like mechanism algorithm is proposed to solve the optimal screening problem of remote sensing data, using the tent chaotic map to construct the initial population, combining with a new local search strategy, and introducing the idea of differential evolutionary algorithm. The experimental results show that the improved algorithm has significant advantages in the optimal screening problem of massive remote sensing data. Compared with the greedy algorithm, the optimal solution of the improved algorithm is increased by about 9.78% on average. Compared with the original algorithm, it can search for the global optimal solution more quickly and has better robustness.https://www.mdpi.com/2076-3417/15/7/3542remote sensing imageoptimizationset covering problemelectromagnetism-like mechanism algorithmtent chaotic mapdifferential evolution algorithm |
| spellingShingle | Yingjie Fang Kun Liu Xun Zhang Gang Lin Huibing Wang Lina Dong Su Li Application of Improved Electromagnetism-like Mechanism Algorithm on Massive Remote Sensing Image Screening Applied Sciences remote sensing image optimization set covering problem electromagnetism-like mechanism algorithm tent chaotic map differential evolution algorithm |
| title | Application of Improved Electromagnetism-like Mechanism Algorithm on Massive Remote Sensing Image Screening |
| title_full | Application of Improved Electromagnetism-like Mechanism Algorithm on Massive Remote Sensing Image Screening |
| title_fullStr | Application of Improved Electromagnetism-like Mechanism Algorithm on Massive Remote Sensing Image Screening |
| title_full_unstemmed | Application of Improved Electromagnetism-like Mechanism Algorithm on Massive Remote Sensing Image Screening |
| title_short | Application of Improved Electromagnetism-like Mechanism Algorithm on Massive Remote Sensing Image Screening |
| title_sort | application of improved electromagnetism like mechanism algorithm on massive remote sensing image screening |
| topic | remote sensing image optimization set covering problem electromagnetism-like mechanism algorithm tent chaotic map differential evolution algorithm |
| url | https://www.mdpi.com/2076-3417/15/7/3542 |
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