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Sep 16, 2024 ， This method considers both meteorological features and short-term and long-term factors of time series to enhance the accuracy and efficiency of imputation.
Sep 26, 2024 ， The K-nearest neighbours (KNN) imputation approach involves identifying the K-nearest neighbours to the observation with missing data and subsequently imputing ...
Sep 14, 2024 ， The study focuses on implementing and evaluating energy consumption prediction models using algorithms like long short-term memory (LSTM), random forest, and ...
5 days ago ， Missing values are imputed using LSTM networks optimized through the Optuna framework. This study emphasizes a data-centric approach in deep learning ...
Sep 25, 2024 ， The former utilizes attention mechanisms to capture the long-range dependencies and intricate patterns of the time-series data. ... using long short-term memory ...
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Sep 16, 2024 ， Journal of Ambient Intelligence and Humanized Computing is a platform for the innovative research and development in the field of ambient intelligence and .
Sep 24, 2024 ， Improved architectures such as the Gated Recurrent Unit (GRU) and Long Short-Term. Memory (LSTM) address these problems. GRU features a simpler structure with ...
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Sep 15, 2024 ， This study offers a comprehensive exploration of trustworthy AI applications in natural disasters, encompassing disaster management, risk assessment, and ...
Sep 25, 2024 ， ML models learn from data and continuously improve with more data available. For example, the long short-term memory (LSTM) is often used in the prediction of ...
Sep 15, 2024 ， With comprehensive coverage of the state of the art in solar resource assessment and forecasting, this handbook serves as a reference document for a wide range ...