Abstract
The traditional remote sensing classification algorithm based on statistics is difficult to obtain high classification accuracy when the ground object environment is complex. To solve this problem, the improved gene expression programming algorithm based on grouping strategy (bs-gep) is applied to the remote sensing image classification problem to avoid the local convergence of the traditional gene expression programming algorithm due to the destruction of population diversity, and solve the problem that it is difficult to obtain high classification accuracy when the ground object condition is complex. The classification rules extracted by the classifier of gene expression programming algorithm based on grouping strategy can be transformed into mathematical expression form and obtain high classification accuracy. Compared with gene expression programming algorithm (GEP), the confusion of classification results is relatively low, compared with maximum likelihood method.
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Lu, J., Cheng, Y. (2022). Application of Bs-Gep Algorithm in Water Conservancy Remote Sensing Image Classification. In: Sugumaran, V., Sreedevi, A.G., Xu , Z. (eds) Application of Intelligent Systems in Multi-modal Information Analytics. ICMMIA 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 138. Springer, Cham. https://doi.org/10.1007/978-3-031-05484-6_139
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DOI: https://doi.org/10.1007/978-3-031-05484-6_139
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