Results 31 to 40 of about 11,734,216 (296)
Short-Term Passenger Flow Prediction of Urban Rail Transit Based on a Combined Deep Learning Model
Applied Sciences, 2022 It is difficult for a single model to simultaneously capture the nonlinear, correlation, and periodicity of data series in the passenger flow prediction of urban rail transit (URT).
Zhongwei Hou +3 more
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Soil Temperature Prediction with Long Short Term Memory (LSTM)
Türk Tarım ve Doğa Bilimleri Dergisi, 2022 Soil temperature not only affects many soil properties, but also has a significant effect on plant development. Knowing and correct estimation of soil temperature is important for both soil management and crop production. The accuracy of temperature forecasts is very important, especially for the countries that stand out with their agriculture-based ...
Orhan İNİK +3 more
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A Hybrid LSTM Neural Network for Energy Consumption Forecasting of Individual Households
IEEE Access, 2019 Irregular human behaviors and univariate datasets remain as two main obstacles of data-driven energy consumption predictions for individual households. In this study, a hybrid deep learning model is proposed combining an ensemble long short term memory ...
Ke Yan +4 more
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Multivariate Time Series Prediction for Loss of Coolant Accidents With a Zigmoid-Based LSTM
Frontiers in Energy Research, 2022 Post-LOCA prediction is of safety significance to NPP, but requires a processing coverage of non-linearity, both short and long-term memory, and multiple system parameters.
Shanshan Gong +4 more
doaj +1 more source
Approximate Computing for Long Short Term Memory (LSTM) Neural Networks
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2018 Long Short Term Memory (LSTM) networks are a class of recurrent neural networks that are widely used for machine learning tasks involving sequences, including machine translation, text generation, and speech recognition. Large-scale LSTMs, which are deployed in many real-world applications, are highly compute intensive.
Sanchari Sen, Anand Raghunathan
openaire +2 more sources
, 2020 <p>Training data sets used to training long short-term memory (LSTM) networks to predict Prisoner's Dilemma actions. </p ...
Glynatsi, Nikoleta E.
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Prediksi Belanja Pemerintah Indonesia Menggunakan Long Short-Term Memory (LSTM)
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), 2021 Estimates of government expenditure for the next period are very important in the government, for instance for the Ministry of Finance of the Republic of Indonesia, because this can be taken into consideration in making policies regarding how much money ...
Sabar Sautomo +1 more
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ENSO prediction based on Long Short-Term Memory (LSTM)
IOP Conference Series: Materials Science and Engineering, 2020 Abstract El Niño-Southern Oscillation (ENSO), as a global climate event with cyclical characteristics, often causes global climate anomalies and produces non-negligible economic and social impacts. Therefore, the prediction and research of ENSO events are important for understanding and solving global climate change issues.
Cao Xiaoqun +5 more
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Short-Term Traffic Speed Prediction Using Hybrid LSTM-SVR Model
, 2023 Traffic speed prediction uses historical data to model traffic patterns and generates forecasts for future steps. As the number of vehicles surges significantly, traffic congestion could negatively affect the quality of life, human health, and the ...
Vu, VH +13 more
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Drug Analogs from Fragment Based Long Short-Term Memory Generative Neural Networks [PDF]
, 2019 Several recent reports have shown that long short-term memory generative neural networks (LSTM) of the type used for grammar learning efficiently learn to write SMILES of drug-like compounds when trained with SMILES from a database of bioactive compounds
Finton, Sirockin +3 more
core +1 more source