… Neural-network-based models for short-term traffic flow forecasting using a hybrid
exponential smoothing and Levenberg-Marquardt algorithm[J]. IEEE Transactions on Intelligent …

… Neural-network-based models for short-term traffic flow forecasting using a hybrid
exponential smoothing and Levenberg-Marquardt algorithm[J]. IEEE Transactions on Intelligent …

… Neural-network-based Models for Short-term Traffic Flow Forecasting Using a Hybrid
Exponential Smoothing and Levenberg-Marquardt Algorithm[J]. IEEE Transactions on Intelligent …

… theory and Markov chain, we propose exponential-smoothing-Markov short-term traffic flow
… Neuralnetwork-based models for short-term traffic flow forecasting using a hybrid exponential …

… precondition to realize the dynamic traffic management. Short -term traffic flow prediction
is an important part of traffic … using a hybrid exponential smoothing and LevenbergMarquardt …

A hybrid short-term load forecasting method based on improved … exponent. However, Guo et
al. (2012) and Huang et al. … 2014), and traffic flow (Li et al., 2013), a hybrid STLF model that …

… Short-term traffic flow prediction with LSTM recurrent neural network. In: Proceedings of the
2017 IEEE 20th International Conference on Intelligent Transportation Systems. Yokohama, …

… simplify the forecasting task for the Long Short-Term Memory … Average or any neural
network-based forecasting method, … more advanced methods like exponential smoothing and the …

… Abstract: For short-term wind power prediction,a class of a class of probabilistic … Short-term
load and wind power forecasting using neural network-based prediction intervals[J]. IEEE …

… Neural-network-based models for short-term traffic flow forecasting using a hybrid
exponential smoothing and Levenberg-Marquardt algorithm[J]. IEEE Transactions on Intelligent …