The primary goal of the distributed economic dispatch challenge is to satisfy meet demand and various operational constraints while minimizing the overall generation cost of all generators. Traditional methods can be ...
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Underwater images play a very important role in projects related to the underwater environment. But in the underwater environment, the R channel attenuation of the RGB image and other reasons make the quality of the i...
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Underwater images play a very important role in projects related to the underwater environment. But in the underwater environment, the R channel attenuation of the RGB image and other reasons make the quality of the i...
ISBN:
(纸本)9781450398343
Underwater images play a very important role in projects related to the underwater environment. But in the underwater environment, the R channel attenuation of the RGB image and other reasons make the quality of the image significantly different from that on land in terms of color and clarity. In order to correct the chromatic aberration of the underwater image and improve the clarity, we propose a DAC method based on the compensation of difference. First, we perform contrast stretching and image denoising on the image. Then extract the details layer and the base layer of the RGB channel of the image respectively, and use the detail layer of the G, B channels with more information to compensate for the detail layer of the R channel. Finally, we optimize the details of the picture through the grayscale world algorithm to obtain the true color of the picture. We compared with various methods in the public underwater dataset UIEB, and it turns out that our method can well solve the problems of chromatic aberration and blur.
The primary goal of the distributed economic dispatch challenge is to satisfy meet demand and various operational constraints while minimizing the overall generation cost of all generators. Traditional methods can be ...
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ISBN:
(数字)9798350384185
ISBN:
(纸本)9798350384192
The primary goal of the distributed economic dispatch challenge is to satisfy meet demand and various operational constraints while minimizing the overall generation cost of all generators. Traditional methods can be ineffective due to unknown cost functions and coupling constraints among different generators. This article introduces a Q-learning algorithm that solves the economic dispatch problem in a distributed manner, efficiently managing multiple coupling constraints. Our apptoach addresses the challenge of dynamic economic dispatch, where both the cost function and resource transfer function are unknown. Numerical simulations validate the algorithm's effectiveness, showcasing its capability to optimize power generation schedules under complex and dynamic conditions.
The separation of single-channel underwater acoustic signals is a challenging problem with practical significance. Few existing studies focus on the source separation problem with unknown numbers of signals, and how t...
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