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Long Short-Term Memory Models
In this chapter, you will learn about recurrent neural networks (RNNs) and long short-term memory (LSTM) models. You will also learn how LSTMs work,...
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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 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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A short-term prediction model of global ionospheric VTEC based on the combination of long short-term memory and convolutional long short-term memory
The ionospheric vertical total electron content (VTEC) is an essential parameter for studying the ionosphere's dynamic variations, and its short-term...
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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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Spatial–positional associations in short-term memory can vanish in long-term memory
Studies on the SPoARC effect have shown that serial information is spatially processed in working memory. However, it remains unknown whether these...
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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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Recognition memory decisions made with short- and long-term retrieval
In the present research, we produce a coherent account of the storage and retrieval processes in short- and long-term event memory, and long-term...
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Reduced benefit from long-term item frequency contributes to short-term memory deficits in dyslexia
Dyslexia, a specific difficulty in acquiring proficient reading, is also characterized by reduced short-term memory (STM) capacity. Extensive...
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Short- and long-term temporal network prediction based on network memory
Temporal networks are networks whose topology changes over time. Two nodes in a temporal network are connected at a discrete time step only if they...
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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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Predicting maintenance through an attention long short-term memory projected model
Long sequence information remains a challenging problem in deep learning nowadays for predicting remaining useful life (RUL). In this work, we...
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Facade Layout Completion with Long Short-Term Memory Networks
In a workflow creating 3D city models, facades of buildings can be reconstructed from oblique aerial images for which the extrinsic and intrinsic...
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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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Detection and identification drones using long short-term memory and Bayesian optimization
This paper proposed a model based on bidirectional Long Short-Term Memory (Bi-LSTM) and Bayesian optimization to detect different drones in different...
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Long short-term memory prediction of user’s locomotion in virtual reality
Nowadays, there is still a challenge in virtual reality to obtain an accurate displacement prediction of the user. This could be a future key element...
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Load Demand Forecasting Using a Long-Short Term Memory Neural Network
Electric power load forecasting is very important for the operation and the planning of a utility company. Decisions of the electric market, electric...
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Linear-layer-enhanced quantum long short-term memory for carbon price forecasting
Accurate carbon price forecasting is important for investors and policymakers to make decisions in the carbon market. With the development of quantum...
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Forecasting Methane Data Using Multivariate Long Short-Term Memory Neural Networks
Over the past few decades, Alberta has witnessed a remarkable expansion in its oil and gas sector. Unfortunately, this growth has come at a cost, as...
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Long Short-Term Memory (LSTM) Based Model for Flood Forecasting in **angjiang River
Due to rapid development, the occurrence of flood has become more and more frequent. However, due to the complex nature and limited knowledge, the...