The teaching–learning-based optimization (tlbo) algorithm is widely recognized for its efficiency and effectiveness in solving optimization problems. However, it often encounters challenges with premature convergence...
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Communication of the satellite images plays a crucial role in many important applications such as change detection, land cover classification, weather prediction etc. The increase in the demand of satellite images ove...
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ISBN:
(纸本)9781509064007
Communication of the satellite images plays a crucial role in many important applications such as change detection, land cover classification, weather prediction etc. The increase in the demand of satellite images over the band limited channel requires good quality compression tools. Currently, the compression standard developed by Joint Photographic Experts Group (JPEG) is the widely used product for the compression of satellite images. Moreover, one of the important elements which influence the performance of JPEG compression standard is the nature of quantization table. The compression ratio and the decompressed image quality arc determined all-together by the quantization table, and hence, the table strongly influences the whole compression performance. The author aims to generate better quantization tables to enhance the compression performance to achieve higher compression ratios while preserving high reconstruction quality for satellite images. A Teaching Learning based optimization (tlbo) technique is employed to promote higher compression performance for satellite images. The aim is to identify optimal quantization tables that contribute to better compression efficiency in terms of image quality indexes Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE). The tlbo based optimization strategy is proposed because it is free from the algorithmic parameters. Experiments were carried out on the three different satellite images. The results demonstrate that the identified optimal quantization tables offer average PSNR gain of about 0.5 dB with the average reduction in MSE of about 10 against the available JPEG quantization table.
In currently studies, the electric vehicle charging piles planning mainly includes two aspects: location and quantity planning. Moreover, the scope of planning mainly includes residential and public parking lot. In th...
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ISBN:
(纸本)9781467388481
In currently studies, the electric vehicle charging piles planning mainly includes two aspects: location and quantity planning. Moreover, the scope of planning mainly includes residential and public parking lot. In this paper, the planning of charging piles is divided into 2 parts for the first time: the centralized charging stations planning and the decentralized charging piles planning. Besides, this paper puts forward a modeling strategy for mileage of EVs considering multi-days spaced charging mode which conforms to the actual user charging habits. Finally, the planning method is applied to a new city planning. Compared with other method, the method of this article pays more attention to the actual situation from the load forecast to the overall planning in the area and puts forward the idea of hierarchical planning for the charging piles for the first time.
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