Artículos de revistas sobre el tema "RNN NETWORK"
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Yin, Qiwei, Ruixun Zhang y XiuLi Shao. "CNN and RNN mixed model for image classification". MATEC Web of Conferences 277 (2019): 02001. http://dx.doi.org/10.1051/matecconf/201927702001.
Texto completoTridarma, Panggih y Sukmawati Nur Endah. "Pengenalan Ucapan Bahasa Indonesia Menggunakan MFCC dan Recurrent Neural Network". JURNAL MASYARAKAT INFORMATIKA 11, n.º 2 (17 de noviembre de 2020): 36–44. http://dx.doi.org/10.14710/jmasif.11.2.34874.
Texto completoMa, Qianli, Zhenxi Lin, Enhuan Chen y Garrison Cottrell. "Temporal Pyramid Recurrent Neural Network". Proceedings of the AAAI Conference on Artificial Intelligence 34, n.º 04 (3 de abril de 2020): 5061–68. http://dx.doi.org/10.1609/aaai.v34i04.5947.
Texto completoMosavat, Majid y Guido Montorsi. "Single-Frequency Network Terrestrial Broadcasting with 5GNR Numerology Using Recurrent Neural Network". Electronics 11, n.º 19 (29 de septiembre de 2022): 3130. http://dx.doi.org/10.3390/electronics11193130.
Texto completoDu, Xiuli, Xiaohui Ding y Fan Tao. "Network Security Situation Prediction Based on Optimized Clock-Cycle Recurrent Neural Network for Sensor-Enabled Networks". Sensors 23, n.º 13 (1 de julio de 2023): 6087. http://dx.doi.org/10.3390/s23136087.
Texto completoChoi, Seongjin, Hwasoo Yeo y Jiwon Kim. "Network-Wide Vehicle Trajectory Prediction in Urban Traffic Networks using Deep Learning". Transportation Research Record: Journal of the Transportation Research Board 2672, n.º 45 (7 de septiembre de 2018): 173–84. http://dx.doi.org/10.1177/0361198118794735.
Texto completoNowak, Mateusz P. y Piotr Pecka. "Routing Algorithms Simulation for Self-Aware SDN". Electronics 11, n.º 1 (29 de diciembre de 2021): 104. http://dx.doi.org/10.3390/electronics11010104.
Texto completoMuhuri, Pramita Sree, Prosenjit Chatterjee, Xiaohong Yuan, Kaushik Roy y Albert Esterline. "Using a Long Short-Term Memory Recurrent Neural Network (LSTM-RNN) to Classify Network Attacks". Information 11, n.º 5 (1 de mayo de 2020): 243. http://dx.doi.org/10.3390/info11050243.
Texto completoParamasivan, Senthil Kumar. "Deep Learning Based Recurrent Neural Networks to Enhance the Performance of Wind Energy Forecasting: A Review". Revue d'Intelligence Artificielle 35, n.º 1 (28 de febrero de 2021): 1–10. http://dx.doi.org/10.18280/ria.350101.
Texto completoYan, Jiapeng, Huifang Kong y Zhihong Man. "Recurrent Neural Network-Based Nonlinear Optimization for Braking Control of Electric Vehicles". Energies 15, n.º 24 (14 de diciembre de 2022): 9486. http://dx.doi.org/10.3390/en15249486.
Texto completoZafri Wan Yahaya, Wan Muhammad, Fadhlan Hafizhelmi Kamaru Zaman y Mohd Fuad Abdul Latip. "Prediction of energy consumption using recurrent neural networks (RNN) and nonlinear autoregressive neural network with external input (NARX)". Indonesian Journal of Electrical Engineering and Computer Science 17, n.º 3 (1 de marzo de 2020): 1215. http://dx.doi.org/10.11591/ijeecs.v17.i3.pp1215-1223.
Texto completoBansal, Bhavana, Aparajita Nanda y Anita Sahoo. "Intelligent Framework With Controlled Behavior for Gene Regulatory Network Reconstruction". International Journal of Information Retrieval Research 12, n.º 1 (enero de 2022): 1–17. http://dx.doi.org/10.4018/ijirr.2022010104.
Texto completoLyu, Shengfei y Jiaqi Liu. "Convolutional Recurrent Neural Networks for Text Classification". Journal of Database Management 32, n.º 4 (octubre de 2021): 65–82. http://dx.doi.org/10.4018/jdm.2021100105.
Texto completoVinayakumar, R., K. P. Soman y Prabaharan Poornachandran. "Evaluation of Recurrent Neural Network and its Variants for Intrusion Detection System (IDS)". International Journal of Information System Modeling and Design 8, n.º 3 (julio de 2017): 43–63. http://dx.doi.org/10.4018/ijismd.2017070103.
Texto completoPark, Jieun, Dokkyun Yi y Sangmin Ji. "Analysis of Recurrent Neural Network and Predictions". Symmetry 12, n.º 4 (13 de abril de 2020): 615. http://dx.doi.org/10.3390/sym12040615.
Texto completoDakwale, Praveen y Christof Monz. "Convolutional over Recurrent Encoder for Neural Machine Translation". Prague Bulletin of Mathematical Linguistics 108, n.º 1 (1 de junio de 2017): 37–48. http://dx.doi.org/10.1515/pralin-2017-0007.
Texto completoYu, Dian y Shouqian Sun. "A Systematic Exploration of Deep Neural Networks for EDA-Based Emotion Recognition". Information 11, n.º 4 (15 de abril de 2020): 212. http://dx.doi.org/10.3390/info11040212.
Texto completoT, Vijayakumar. "NEURAL NETWORK ANALYSIS FOR TUMOR INVESTIGATION AND CANCER PREDICTION". December 2019 2019, n.º 02 (18 de diciembre de 2019): 89–98. http://dx.doi.org/10.36548/jei.2019.2.004.
Texto completoT, Vijayakumar. "NEURAL NETWORK ANALYSIS FOR TUMOR INVESTIGATION AND CANCER PREDICTION". December 2019 2019, n.º 02 (18 de diciembre de 2019): 89–98. http://dx.doi.org/10.36548/jes.2019.2.004.
Texto completoAribowo, Widi. "ELMAN-RECURRENT NEURAL NETWORK FOR LOAD SHEDDING OPTIMIZATION". SINERGI 24, n.º 1 (14 de enero de 2020): 29. http://dx.doi.org/10.22441/sinergi.2020.1.005.
Texto completoYoko, Kuncoro, Viny Christanti Mawardi y Janson Hendryli. "SISTEM PERINGKAS OTOMATIS ABSTRAKTIF DENGAN MENGGUNAKAN RECURRENT NEURAL NETWORK". Computatio : Journal of Computer Science and Information Systems 2, n.º 1 (22 de mayo de 2018): 65. http://dx.doi.org/10.24912/computatio.v2i1.1481.
Texto completoWu, Yijun y Yonghong Qin. "Machine translation of English speech: Comparison of multiple algorithms". Journal of Intelligent Systems 31, n.º 1 (1 de enero de 2022): 159–67. http://dx.doi.org/10.1515/jisys-2022-0005.
Texto completoHazazi, Muhammad Asaduddin y Agus Sihabuddin. "Extended Kalman Filter In Recurrent Neural Network: USDIDR Forecasting Case Study". IJCCS (Indonesian Journal of Computing and Cybernetics Systems) 13, n.º 3 (31 de julio de 2019): 293. http://dx.doi.org/10.22146/ijccs.47802.
Texto completoKamyab, Marjan, Guohua Liu, Abdur Rasool y Michael Adjeisah. "ACR-SA: attention-based deep model through two-channel CNN and Bi-RNN for sentiment analysis". PeerJ Computer Science 8 (17 de marzo de 2022): e877. http://dx.doi.org/10.7717/peerj-cs.877.
Texto completoZhu, Zhenshu, Yuming Bo y Changhui Jiang. "A MEMS Gyroscope Noise Suppressing Method Using Neural Architecture Search Neural Network". Mathematical Problems in Engineering 2019 (21 de noviembre de 2019): 1–9. http://dx.doi.org/10.1155/2019/5491243.
Texto completoSubba, Sanjeev, Nawaraj Paudel y Tej Bahadur Shahi. "Nepali Text Document Classification Using Deep Neural Network". Tribhuvan University Journal 33, n.º 1 (30 de junio de 2019): 11–22. http://dx.doi.org/10.3126/tuj.v33i1.28677.
Texto completoWang, Yung-Chung, Yi-Chun Houng, Han-Xuan Chen y Shu-Ming Tseng. "Network Anomaly Intrusion Detection Based on Deep Learning Approach". Sensors 23, n.º 4 (15 de febrero de 2023): 2171. http://dx.doi.org/10.3390/s23042171.
Texto completoWinanto, Eko Arip, Kurniabudi Kurniabudi, Sharipuddin Sharipuddin, Ibnu Sani Wijaya y Dodi Sandra. "Deteksi Serangan pada Jaringan Kompleks IoT menggunakan Recurrent Neural Network". JURIKOM (Jurnal Riset Komputer) 9, n.º 6 (30 de diciembre de 2022): 1996. http://dx.doi.org/10.30865/jurikom.v9i6.5298.
Texto completoJi, Junjie, Yongzhang Zhou, Qiuming Cheng, Shoujun Jiang y Shiting Liu. "Landslide Susceptibility Mapping Based on Deep Learning Algorithms Using Information Value Analysis Optimization". Land 12, n.º 6 (25 de mayo de 2023): 1125. http://dx.doi.org/10.3390/land12061125.
Texto completoHardy, N. F. y Dean V. Buonomano. "Encoding Time in Feedforward Trajectories of a Recurrent Neural Network Model". Neural Computation 30, n.º 2 (febrero de 2018): 378–96. http://dx.doi.org/10.1162/neco_a_01041.
Texto completoMohd Ruslan, Muhammad Faridzul Faizal y Mohd Firdaus Hassan. "Unbalance Failure Recognition Using Recurrent Neural Network". International Journal of Automotive and Mechanical Engineering 19, n.º 2 (28 de junio de 2022): 9668–80. http://dx.doi.org/10.15282/ijame.19.2.2022.04.0746.
Texto completoAdeel, Ahsan, Hadi Larijani, Abbas Javed y Ali Ahmadinia. "Impact of Learning Algorithms on Random Neural Network based Optimization for LTE-UL Systems". Network Protocols and Algorithms 7, n.º 3 (30 de noviembre de 2015): 157. http://dx.doi.org/10.5296/npa.v7i3.8295.
Texto completoCheng, Yepeng, Zuren Liu y Yasuhiko Morimoto. "Attention-Based SeriesNet: An Attention-Based Hybrid Neural Network Model for Conditional Time Series Forecasting". Information 11, n.º 6 (5 de junio de 2020): 305. http://dx.doi.org/10.3390/info11060305.
Texto completoReddy, Mr G. Sekhar, A. Sahithi, P. Harsha Vardhan y P. Ushasri. "Conversion of Sign Language Video to Text and Speech". International Journal for Research in Applied Science and Engineering Technology 10, n.º 5 (31 de mayo de 2022): 159–64. http://dx.doi.org/10.22214/ijraset.2022.42078.
Texto completoZhu, Jian-Hua, Musharraf M. Zaman y Scott A. Anderson. "Modeling of soil behavior with a recurrent neural network". Canadian Geotechnical Journal 35, n.º 5 (1 de octubre de 1998): 858–72. http://dx.doi.org/10.1139/t98-042.
Texto completoRathika, M., P. Sivakumar, K. Ramash Kumar y Ilhan Garip. "Cooperative Communications Based on Deep Learning Using a Recurrent Neural Network in Wireless Communication Networks". Mathematical Problems in Engineering 2022 (21 de diciembre de 2022): 1–12. http://dx.doi.org/10.1155/2022/1864290.
Texto completoVenturini, M. "Simulation of Compressor Transient Behavior Through Recurrent Neural Network Models". Journal of Turbomachinery 128, n.º 3 (1 de febrero de 2005): 444–54. http://dx.doi.org/10.1115/1.2183315.
Texto completoLiao, Zhehao. "Comparative analysis between application of transformer and recurrent neural network in speech recognition". Applied and Computational Engineering 6, n.º 1 (14 de junio de 2023): 629–34. http://dx.doi.org/10.54254/2755-2721/6/20230879.
Texto completoAlkahtani, Hasan, Theyazn H. H. Aldhyani y Mohammed Al-Yaari. "Adaptive Anomaly Detection Framework Model Objects in Cyberspace". Applied Bionics and Biomechanics 2020 (9 de diciembre de 2020): 1–14. http://dx.doi.org/10.1155/2020/6660489.
Texto completoJiang, Tingting y Xiang Gao. "Deep Learning of Subject Context in Ideological and Political Class Based on Recursive Neural Network". Computational Intelligence and Neuroscience 2022 (30 de septiembre de 2022): 1–8. http://dx.doi.org/10.1155/2022/8437548.
Texto completoAlbahar, Marwan Ali. "Recurrent Neural Network Model Based on a New Regularization Technique for Real-Time Intrusion Detection in SDN Environments". Security and Communication Networks 2019 (18 de noviembre de 2019): 1–9. http://dx.doi.org/10.1155/2019/8939041.
Texto completoKrishnan, Surenthiran, Pritheega Magalingam y Roslina Ibrahim. "Hybrid deep learning model using recurrent neural network and gated recurrent unit for heart disease prediction". International Journal of Electrical and Computer Engineering (IJECE) 11, n.º 6 (1 de diciembre de 2021): 5467. http://dx.doi.org/10.11591/ijece.v11i6.pp5467-5476.
Texto completoBukhsh, Madiha, Muhammad Saqib Ali, Abdullah Alourani, Khlood Shinan, Muhammad Usman Ashraf, Abdul Jabbar y Weiqiu Chen. "Long Short-Term Memory Recurrent Neural Network Approach for Approximating Roots (Eigen Values) of Transcendental Equation of Cantilever Beam". Applied Sciences 13, n.º 5 (23 de febrero de 2023): 2887. http://dx.doi.org/10.3390/app13052887.
Texto completoWang, Xintong y Chuangang Zhao. "A 2D Convolutional Gating Mechanism for Mandarin Streaming Speech Recognition". Information 12, n.º 4 (12 de abril de 2021): 165. http://dx.doi.org/10.3390/info12040165.
Texto completoKim, Deageon. "Text Classification Based on Neural Network Fusion". Tehnički glasnik 17, n.º 3 (19 de julio de 2023): 359–66. http://dx.doi.org/10.31803/tg-20221228154330.
Texto completoYu, Chih-Chang y Yufeng (Leon) Wu. "Early Warning System for Online STEM Learning—A Slimmer Approach Using Recurrent Neural Networks". Sustainability 13, n.º 22 (11 de noviembre de 2021): 12461. http://dx.doi.org/10.3390/su132212461.
Texto completoHo, Namgyu y Yoon-Chul Kim. "Estimation of Cardiac Short Axis Slice Levels with a Cascaded Deep Convolutional and Recurrent Neural Network Model". Tomography 8, n.º 6 (14 de noviembre de 2022): 2749–60. http://dx.doi.org/10.3390/tomography8060229.
Texto completoMargasov, A. O. "Neural ordinary differential equations and their probabilistic extension". Proceedings of the Komi Science Centre of the Ural Division of the Russian Academy of Sciences 6 (2021): 14–19. http://dx.doi.org/10.19110/1994-5655-2021-6-14-19.
Texto completoYang, Fushen, Changshun Du y Lei Huang. "Ensemble Sentiment Analysis Method based on R-CNN and C-RNN with Fusion Gate". International Journal of Computers Communications & Control 14, n.º 2 (14 de abril de 2019): 272–85. http://dx.doi.org/10.15837/ijccc.2019.2.3375.
Texto completoKustiyo, Aziz, Mukhlis Mukhlis y Aries Suharso. "Model Recurent Neural Network untuk Peramalan Produksi Tebu Nasional". BINA INSANI ICT JOURNAL 9, n.º 1 (28 de junio de 2022): 1. http://dx.doi.org/10.51211/biict.v9i1.1744.
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