Short-Term Wind Speed Forecasting With Principle-Subordinate Predictor Based on Conv-LSTM and Improved BPNN
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.2982839
Abstract: To improve the accuracy of short term wind speed forecasting, a novel principle-subordinate prediction model based on Conv-LSTM network and BPNN is designed in this paper. The proposed model combines deep learning algorithms and improved… read more here.
Keywords: speed; speed forecasting; model; prediction ... See more keywords
A Deep Learning Model with Conv-LSTM Networks for Subway Passenger Congestion Delay Prediction
Sign Up to like & getrecommendations! Published in 2021 at "Journal of Advanced Transportation"
DOI: 10.1155/2021/6645214
Abstract: When urban rail transit is faced with a large number of commuter passengers during peak periods, passengers are often waiting for the next train because the subway is running at full load, which causes delays… read more here.
Keywords: congestion delay; conv lstm; delay; congestion ... See more keywords
Interpreting Conv-LSTM for Spatio-Temporal Soil Moisture Prediction in China
Sign Up to like & getrecommendations! Published in 2023 at "Agriculture"
DOI: 10.3390/agriculture13050971
Abstract: Soil moisture (SM) is a key variable in Earth system science that affects various hydrological and agricultural processes. Convolutional long short-term memory (Conv-LSTM) networks are widely used deep learning models for spatio-temporal SM prediction, but… read more here.
Keywords: soil moisture; lstm; prediction; conv lstm ... See more keywords
Flight Delay Regression Prediction Model Based on Att-Conv-LSTM
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DOI: 10.3390/e25050770
Abstract: Accurate prediction results can provide an excellent reference value for the prevention of large-scale flight delays. Most of the currently available regression prediction algorithms use a single time series network to extract features, with less… read more here.
Keywords: lstm; prediction; flight delay; model ... See more keywords