Results 1 to 10 of about 349,230 (288)
Exploring Efficient Neural Architectures for Linguistic–Acoustic Mapping in Text-To-Speech [PDF]
Applied Sciences, 2019 Conversion from text to speech relies on the accurate mapping from linguistic to acoustic symbol sequences, for which current practice employs recurrent statistical models such as recurrent neural networks. Despite the good performance of such models (in
Santiago Pascual +2 more
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Comparison of Novel Recurrent Neural Network Over Artificial Neural network in Predicting Email spammers with improved accuracy [PDF]
E3S Web of Conferences, 2023 The main aim is to compare Novel Recurrent Neural Network over Artificial Neural Network in predicting Email spammers with improved accuracy. Material and Methods : This research study contains two groups namely Novel Recurrent Neural Network and ...
Neeharika Chillakuru, Kalaiarasi S.
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Survey on Evolutionary Recurrent Neural Networks [PDF]
Jisuanji kexue, 2023 Evolutionary computation utilizes natural selection mechanisms and genetic laws in the process of biological evolution to solve optimization problems.The accuracy and efficiency of the evolutionary recurrent neural network model depends on the ...
HU Zhongyuan, XUE Yu, ZHA Jiajie
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Research on recurrent neural network model based on weight activity evaluation [PDF]
ITM Web of Conferences, 2022 Given the complex structure and parameter redundancy of recurrent neural networks such as LSTM, related research and analysis on the structure of recurrent neural networks have been done.
Zhang Cheng +5 more
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, 2022 AbstractThis chapter considers recurrent neural (RN) networks. These are special network architectures that are useful for time-series modeling, e.g., applied to time-series forecasting. We study the most popular RN networks which are the long short-term memory (LSTM) networks and the gated recurrent unit (GRU) networks.
Amit Kumar Tyagi, Ajith Abraham
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Recurrent neural networks [PDF]
Scholarpedia, 2013 This chapter presents an introduction to recurrent neural networks for readers familiar with artificial neural networks in general, and multi-layer perceptrons trained with gradient descent algorithms (back-propagation) in particular. A recurrent neural network (RNN) is an artificial neural network with internal loops.
Sajid A. Marhon +2 more
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Recurrent neural network optimization for wind turbine condition prognosis
Diagnostyka, 2022 This research focuses on employing Recurrent Neural Networks (RNN) to prognosis a wind turbine operation’s health from collected vibration time series data, by using several memory cell variations, including Long Short Time Memory (LSTM), Bilateral LSTM (
Kerboua Adlen, Kelaiaia Ridha
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Electrical engineering & Electromechanics, 2022 Purpose. This article proposes a new control strategy for static synchronous compensator in utility grid system. The proposed photovoltaic fed static synchronous compensator is utilized along with recurrent neural network based reference voltage ...
T. Praveen Kumar +2 more
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Recurrent Neural Network Grammars [PDF]
Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2016 We introduce recurrent neural network grammars, probabilistic models of sentences with explicit phrase structure. We explain efficient inference procedures that allow application to both parsing and language modeling. Experiments show that they provide better parsing in English than any single previously published supervised generative model and better
Dyer, Chris +3 more
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Jurnal Teknologi Informasi dan Ilmu Komputer, 2021 Hadis merupakan sumber hukum dan pedoman kedua bagi umat Islam setelah Al-Qur’an dan banyak sekali hadis yang telah diriwayatkan oleh para ahli hadis selama ini.
Muhammad Yuslan Abu Bakar +1 more
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