Results 31 to 40 of about 1,476,903 (264)
Short-Term Residential Load Forecasting Based on LSTM Recurrent Neural Network
IEEE Transactions on Smart Grid, 2019 As the power system is facing a transition toward a more intelligent, flexible, and interactive system with higher penetration of renewable energy generation, load forecasting, especially short-term load forecasting for individual electric customers ...
Weicong Kong +5 more
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SeqSleepNet: End-to-End Hierarchical Recurrent Neural Network for Sequence-to-Sequence Automatic Sleep Staging [PDF]
IEEE transactions on neural systems and rehabilitation engineering, 2018 Automatic sleep staging has been often treated as a simple classification problem that aims at determining the label of individual target polysomnography epochs one at a time.
Huy Phan +4 more
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Clustering Based on Continuous Hopfield Network
Mathematics, 2022 Clustering aims to group n data samples into k clusters. In this paper, we reformulate the clustering problem into an integer optimization problem and propose a recurrent neural network with n×k neurons to solve it. We prove the stability and convergence
Yao Xiao +3 more
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General Recurrent Neural Network for Solving Generalized Linear Matrix Equation
Complexity, 2017 This brief proposes a general framework of the nonlinear recurrent neural network for solving online the generalized linear matrix equation (GLME) with global convergence property. If the linear activation function is utilized, the neural state matrix of
Zhan Li, Hong Cheng, Hongliang Guo
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Sensors, 2021 In this study, a scheme of remaining useful lifetime (RUL) prognosis from raw acoustic emission (AE) data is presented to predict the concrete structure’s failure before its occurrence, thus possibly prolong its service life and minimizing the risk of ...
Tuan-Khai Nguyen +2 more
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Neural Approximators for Variable-Order Fractional Calculus Operators (VO-FC)
IEEE Access, 2022 The paper presents research on the approximation of variable-order fractional operators by recurrent neural networks. The research focuses on two basic variable-order fractional operators, i.e., integrator and differentiator.
Bartosz Puchalski
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Document Modeling with Gated Recurrent Neural Network for Sentiment Classification
Conference on Empirical Methods in Natural Language Processing, 2015 Document level sentiment classification remains a challenge: encoding the intrinsic relations between sentences in the semantic meaning of a document. To address this, we introduce a neural network model to learn vector-based document representation in a
Duyu Tang, Bing Qin, Ting Liu
semanticscholar +1 more source
Компютерні системи та інформаційні технології, 2023 The connectionist-metaheuristic approach solved the urgent task of using new approaches to analyze the foreign direct investment and macroeconomic indicators that affect the volume of their attraction to a particular country in the world economy.
Maryna LESHCHENKO +3 more
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Haze Prediction Model Using Deep Recurrent Neural Network
Atmosphere, 2021 In recent years, haze pollution is frequent, which seriously affects daily life and production process. The main factors to measure the degree of smoke pollution are the concentrations of PM2.5 and PM10.
Kailin Shang +7 more
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A new approach to seasonal energy consumption forecasting using temporal convolutional networks
Results in Engineering, 2023 There has been a significant increase in the attention paid to resource management in smart grids, and several energy forecasting models have been published in the literature.
Abdul Khalique Shaikh +4 more
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