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Published in 2025 at "IEEE Access"
DOI: 10.1109/access.2025.3595912
Abstract: In response to the challenges posed by large data fluctuations, complex influencing factors, and the need for high forecasting accuracy in short-term power load forecasting, this paper proposes a combined convolutional neural network-bidirectional gated loop…
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Keywords:
load;
cnn bigru;
load forecasting;
power load ... See more keywords
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Published in 2025 at "IEEE Sensors Journal"
DOI: 10.1109/jsen.2025.3596781
Abstract: Accurate relative positioning is essential for the deployment of an intelligent transportation system. However, in complex environments such as urban canyons and tunnels, the global positioning system (GPS) signals are often blocked or interrupted, resulting…
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Keywords:
bigru attention;
cnn bigru;
attention;
model ... See more keywords
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Published in 2025 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2025.3562444
Abstract: The Martian polar-layered deposits (PLDs), composed primarily of water ice with a small fraction of dust, form the upper structure of Mars’ northern plains. The thickness and dust content of these deposits are crucial for…
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Keywords:
layer;
cnn bigru;
dust content;
ice ... See more keywords
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Published in 2025 at "Frontiers in Neuroinformatics"
DOI: 10.3389/fninf.2025.1618050
Abstract: Electroencephalogram (EEG) signal analysis plays a vital role in diagnosing and monitoring alcoholism, where accurate classification of individuals into alcoholic and control groups is essential. However, the inherent noise and complexity of EEG signals pose…
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Keywords:
classification;
dwt cnn;
cnn bigru;
alcoholic control ... See more keywords
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Published in 2024 at "Agriculture"
DOI: 10.3390/agriculture14091556
Abstract: One of the primary factors in the hydrological cycle is reference evapotranspiration (ET0). The prediction of ET0 is crucial to manage irrigation water in agriculture under climate change; however, little research has been conducted on…
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Keywords:
bigru attention;
cnn bigru;
sao cnn;
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Published in 2025 at "Energies"
DOI: 10.3390/en18102523
Abstract: Unconventional reservoirs are characterized by intricate fluid-phase behaviors, and physics-based shale oil well productivity prediction models often exhibit substantial deviations due to oversimplified theoretical frameworks and challenges in parameter acquisition. Under these circumstances, data-driven approaches…
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Keywords:
productivity prediction;
cnn bigru;
sequence;
model ... See more keywords