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journal article·2025-03-24Open access

Application of Improved Electromagnetism-like Mechanism Algorithm on Massive Remote Sensing Image Screening

Yingjie Fang, Kun Liu, Xun Zhang, Gang Lin, Huibing Wang, Lina Dong, Su Li

Applied Sciences· Volume 15· Issue 7
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Source abstract

Abstract

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.
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Research context

OpenAlex topics: Remote Sensing and Land Use

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

College of Computer and Artificial Intelligence, Beijing Technology and Business University, Beijing 100048, China

Land Satellite Remote Sensing Application Center, Ministry of Natural Resources of the People’s Republic of China, Beijing 100048, China

Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China

College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China

Key Laboratory of Coupling Processes and Effects of Natural Resource Elements, Ministry of Natural Resources, Beijing 100055, China

College of Geoscience and Surveying Engineering, China University of Mining & Technology (Beijing), Beijing 100083, China

Funding

National Key Research and Development Program of China · National Natural Science Foundation of China · Project of Social Science Foundation of Xinjiang Uygur Autonomous Region · Project of Natural Science Foundation of Xinjiang Uygur Autonomous Region · Beijing Social Science Foundation

References (26)

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