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Bi-directional Long Short Term Memory Neural Network for Short-Term Traffic Speed Prediction Using Gravitational Search Algorithm
Traffic speed prediction has implications for urban planning, congestion reduction, and intelligent control systems. To maintain a uniform traffic...
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Short-term forecasting electricity load by long short-term memory and reinforcement learning for optimization of hyper-parameters
Electricity load forecasting is an essential operation of the power system. Deep learning is used to improve accurate electricity load forecasting....
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Long-term and short-term memory networks based on forgetting memristors
The hardware circuit of neural network based on forgetting memristors not only has the characteristics of high computational efficiency and low power...
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Short-Term Load Forecasting for Commercial Building Using Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) Network with Similar Day Selection Model
Load forecasting is essential in power systems for reliable and efficient energy planning and operation. Commercial buildings usually account for 20%...
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Very Short-Term Forecasting of Wind Power Based on Transformer
Accurate wind power forecasting is crucial for the stability of modern power systems and fostering wind power utilization. However, very short-term...
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Expressway Short-Term Traffic Flow Prediction Based on CNN-LSTM
In recent years, with the continuous improvement of people's quality of life, the purchase of motor vehicles has become more and more. Accompanied by...
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Exploring Deep Learning Approaches for Short-Term Passenger Demand Prediction
An accurate short-term passenger demand forecast makes a contribution to the coordination of traffic supply and demand. Forecasting the short-term...
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A Sequential Recommendation Model for Balancing Long- and Short-Term Benefits
Typically, user behaviour occurs continuously, and considering this dynamic sequence correlation can lead to more accurate recommendations....
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Short-Term Load Forecasting Model Considering Multiple Time Scales
Most of the existing load forecasting methods are based on a single time scale for analysis and research, while the load power sequence has an...
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Very Short-Term Power Forecasting for Photovoltaic Power Plants Using a Simple LSTM Model Based on Short-Term Historical Datasets: Case Study
Prediction of small-scale and even large-scale solar energy is a hot research field. In fact, the intermittent nature of solar energy can disrupt the...
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A Deviation-Minimization Approach to Short-Term Underground Mine Schedule Optimization
Production forecasts derived from the medium-term schedule represent the best path forward for underground mining operations to achieve corporate and...
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Short-Term Traffic Speed Prediction for Multiple Road Segments
Short-term traffic prediction has been an essential part of real-time applications in modern transportation systems for the last few decades. Despite...
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Federated quantum long short-term memory (FedQLSTM)
Quantum federated learning (QFL) can facilitate collaborative learning across multiple clients using quantum machine learning (QML) models, while...
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Develo** a Novel Long Short-Term Memory Networks with Seasonal Wavelet Transform for Long-Term Wind Power Output Forecasting
Long-term wind power forecasting is a challenging endeavor that requires predictions that span years into the future. Accurate forecasting is crucial...
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Short-Term Traffic Speed Prediction Using Hybrid LSTM-SVR Model
Traffic speed prediction uses historical data to model traffic patterns and generates forecasts for future steps. As the number of vehicles surges...
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Application of Time Series Regression, Double Seasonal ARIMA, and Long Short-Term Memory for Short-Term Electricity Load Forecasting
Electricity load must be accurately estimated since electricity is non-storable. If electricity is generated more than customer’s demand, it will be...
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Short-Term Prediction of COVID-19 Deaths in Argentina
This paper proposes a dynamic model for accurate short-term prediction of the coronavirus disease (COVID-19) death rates in Argentina. For this...
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State of Charge Estimation of Lithium-Ion Batteries Using Long Short-Term Memory and Bi-directional Long Short-Term Memory Neural Networks
This research proposes a data-driven method for estimating the state of charge of lithium-ion batteries using two neural networks, namely long...
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Short-term wind power prediction based on ICEEMDAN-Correlation reconstruction and BWO-BiLSTM
To solve the problems of high volatility and low prediction accuracy of wind farm output power, this paper proposes a short-term wind power...
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Study on Short-Term Prediction of Roll in Beam Sea
The formula to determine the roll angle for structural strength assessment in ClassNK’s Technical Rule and Guidance gives a value based upon maximum...