Articoli di riviste sul tema "LSTM Neural networks"
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Bakir, Houda, Ghassen Chniti e Hédi Zaher. "E-Commerce Price Forecasting Using LSTM Neural Networks". International Journal of Machine Learning and Computing 8, n. 2 (aprile 2018): 169–74. http://dx.doi.org/10.18178/ijmlc.2018.8.2.682.
Yu, Yong, Xiaosheng Si, Changhua Hu e Jianxun Zhang. "A Review of Recurrent Neural Networks: LSTM Cells and Network Architectures". Neural Computation 31, n. 7 (luglio 2019): 1235–70. http://dx.doi.org/10.1162/neco_a_01199.
Kalinin, Maxim, Vasiliy Krundyshev e Evgeny Zubkov. "Estimation of applicability of modern neural network methods for preventing cyberthreats to self-organizing network infrastructures of digital economy platforms",. SHS Web of Conferences 44 (2018): 00044. http://dx.doi.org/10.1051/shsconf/20184400044.
Zhang, Chuanwei, Xusheng Xu, Yikun Li, Jing Huang, Chenxi Li e Weixin Sun. "Research on SOC Estimation Method for Lithium-Ion Batteries Based on Neural Network". World Electric Vehicle Journal 14, n. 10 (2 ottobre 2023): 275. http://dx.doi.org/10.3390/wevj14100275.
Sridhar, C., e Aniruddha Kanhe. "Performance Comparison of Various Neural Networks for Speech Recognition". Journal of Physics: Conference Series 2466, n. 1 (1 marzo 2023): 012008. http://dx.doi.org/10.1088/1742-6596/2466/1/012008.
Wan, Yingliang, Hong Tao e Li Ma. "Forecasting Zhejiang Province's GDP Using a CNN-LSTM Model". Frontiers in Business, Economics and Management 13, n. 3 (5 marzo 2024): 233–35. http://dx.doi.org/10.54097/bmq2dy63.
Liu, David, e An Wei. "Regulated LSTM Artificial Neural Networks for Option Risks". FinTech 1, n. 2 (2 giugno 2022): 180–90. http://dx.doi.org/10.3390/fintech1020014.
Pal, Subarno, Soumadip Ghosh e Amitava Nag. "Sentiment Analysis in the Light of LSTM Recurrent Neural Networks". International Journal of Synthetic Emotions 9, n. 1 (gennaio 2018): 33–39. http://dx.doi.org/10.4018/ijse.2018010103.
Kabildjanov, A. S., Ch Z. Okhunboboeva e S. Yo Ismailov. "Intelligent forecasting of growth and development of fruit trees by deep learning recurrent neural networks". IOP Conference Series: Earth and Environmental Science 1206, n. 1 (1 giugno 2023): 012015. http://dx.doi.org/10.1088/1755-1315/1206/1/012015.
Yu, Dian, e Shouqian Sun. "A Systematic Exploration of Deep Neural Networks for EDA-Based Emotion Recognition". Information 11, n. 4 (15 aprile 2020): 212. http://dx.doi.org/10.3390/info11040212.
Zhang, Chun-Xiang, Shu-Yang Pang, Xue-Yao Gao, Jia-Qi Lu e Bo Yu. "Attention Neural Network for Biomedical Word Sense Disambiguation". Discrete Dynamics in Nature and Society 2022 (10 gennaio 2022): 1–14. http://dx.doi.org/10.1155/2022/6182058.
Mao, Congmin, e Sujing Liu. "A Study on Speech Recognition by a Neural Network Based on English Speech Feature Parameters". Journal of Advanced Computational Intelligence and Intelligent Informatics 28, n. 3 (20 maggio 2024): 679–84. http://dx.doi.org/10.20965/jaciii.2024.p0679.
Mountzouris, Konstantinos, Isidoros Perikos e Ioannis Hatzilygeroudis. "Speech Emotion Recognition Using Convolutional Neural Networks with Attention Mechanism". Electronics 12, n. 20 (23 ottobre 2023): 4376. http://dx.doi.org/10.3390/electronics12204376.
Wan, Huaiyu, Shengnan Guo, Kang Yin, Xiaohui Liang e Youfang Lin. "CTS-LSTM: LSTM-based neural networks for correlatedtime series prediction". Knowledge-Based Systems 191 (marzo 2020): 105239. http://dx.doi.org/10.1016/j.knosys.2019.105239.
Xu, Lingfeng, Xiang Chen, Shuai Cao, Xu Zhang e Xun Chen. "Feasibility Study of Advanced Neural Networks Applied to sEMG-Based Force Estimation". Sensors 18, n. 10 (25 settembre 2018): 3226. http://dx.doi.org/10.3390/s18103226.
Blinov, I., V. Miroshnyk e V. Sychova. "Short-term forecasting of electricity imbalances using artificial neural networks". IOP Conference Series: Earth and Environmental Science 1254, n. 1 (1 ottobre 2023): 012029. http://dx.doi.org/10.1088/1755-1315/1254/1/012029.
Pavlatos, Christos, Evangelos Makris, Georgios Fotis, Vasiliki Vita e Valeri Mladenov. "Enhancing Electrical Load Prediction Using a Bidirectional LSTM Neural Network". Electronics 12, n. 22 (15 novembre 2023): 4652. http://dx.doi.org/10.3390/electronics12224652.
Song, Dazhi, e Dazhi Song. "Stock Price Prediction based on Time Series Model and Long Short-term Memory Method". Highlights in Business, Economics and Management 24 (22 gennaio 2024): 1203–10. http://dx.doi.org/10.54097/e75xgk49.
Gers, Felix A., Jürgen Schmidhuber e Fred Cummins. "Learning to Forget: Continual Prediction with LSTM". Neural Computation 12, n. 10 (1 ottobre 2000): 2451–71. http://dx.doi.org/10.1162/089976600300015015.
Wei, Jun, Fan Yang, Xiao-Chen Ren e Silin Zou. "A Short-Term Prediction Model of PM2.5 Concentration Based on Deep Learning and Mode Decomposition Methods". Applied Sciences 11, n. 15 (27 luglio 2021): 6915. http://dx.doi.org/10.3390/app11156915.
Bucci, Andrea. "Realized Volatility Forecasting with Neural Networks". Journal of Financial Econometrics 18, n. 3 (2020): 502–31. http://dx.doi.org/10.1093/jjfinec/nbaa008.
Du, Shaohui, Zhenghan Chen, Haoyan Wu, Yihong Tang e YuanQing Li. "Image Recommendation Algorithm Combined with Deep Neural Network Designed for Social Networks". Complexity 2021 (2 luglio 2021): 1–9. http://dx.doi.org/10.1155/2021/5196190.
Singh, Arjun, Shashi Kant Dargar, Amit Gupta, Ashish Kumar, Atul Kumar Srivastava, Mitali Srivastava, Pradeep Kumar Tiwari e Mohammad Aman Ullah. "Evolving Long Short-Term Memory Network-Based Text Classification". Computational Intelligence and Neuroscience 2022 (21 febbraio 2022): 1–11. http://dx.doi.org/10.1155/2022/4725639.
Zhang, Cheng, Luying Li, Yanmei Liu, Xuejiao Luo, Shangguan Song e Dingchun Xia. "Research on recurrent neural network model based on weight activity evaluation". ITM Web of Conferences 47 (2022): 02046. http://dx.doi.org/10.1051/itmconf/20224702046.
Mero, Kevin, Nelson Salgado, Jaime Meza, Janeth Pacheco-Delgado e Sebastián Ventura. "Unemployment Rate Prediction Using a Hybrid Model of Recurrent Neural Networks and Genetic Algorithms". Applied Sciences 14, n. 8 (10 aprile 2024): 3174. http://dx.doi.org/10.3390/app14083174.
Chuang, Chia-Chun, Chien-Ching Lee, Chia-Hong Yeng, Edmund-Cheung So e Yeou-Jiunn Chen. "Attention Mechanism-Based Convolutional Long Short-Term Memory Neural Networks to Electrocardiogram-Based Blood Pressure Estimation". Applied Sciences 11, n. 24 (17 dicembre 2021): 12019. http://dx.doi.org/10.3390/app112412019.
Tra, Nguyen Ngoc, Ho Phuoc Tien, Nguyen Thanh Dat e Nguyen Ngoc Vu. "VN-INDEX TREND PREDICTION USING LONG-SHORT TERM MEMORY NEURAL NETWORKS". Journal of Science and Technology: Issue on Information and Communications Technology 17, n. 12.2 (9 dicembre 2019): 61. http://dx.doi.org/10.31130/ict-ud.2019.94.
Nguyen, Viet-Hung, Minh-Tuan Nguyen, Jeongsik Choi e Yong-Hwa Kim. "NLOS Identification in WLANs Using Deep LSTM with CNN Features". Sensors 18, n. 11 (20 novembre 2018): 4057. http://dx.doi.org/10.3390/s18114057.
Nogueira Filho, Francisco José Matos, Francisco de Assis Souza Filho, Victor Costa Porto, Renan Vieira Rocha, Ályson Brayner Sousa Estácio e Eduardo Sávio Passos Rodrigues Martins. "Deep Learning for Streamflow Regionalization for Ungauged Basins: Application of Long-Short-Term-Memory Cells in Semiarid Regions". Water 14, n. 9 (19 aprile 2022): 1318. http://dx.doi.org/10.3390/w14091318.
Liu, Lunhaojie, Wen Fu, Xingao Bian e Juntao Fei. "Adaptive Intelligent Sliding Mode Control of a Dynamic System with a Long Short-Term Memory Structure". Mathematics 10, n. 7 (6 aprile 2022): 1197. http://dx.doi.org/10.3390/math10071197.
Becerra Muriel, Cristian. "Forecasting the Future Value of a Colombian Investment Fund with LSTM Recurrent Neural Networks (LSTM)". System Analysis & Mathematical Modeling 6, n. 1 (30 marzo 2024): 78–88. http://dx.doi.org/10.17150/2713-1734.2024.6(1).78-88.
Zhang, Feizhou, Ke Shang, Lei Yan, Haijing Nan e Zicong Miao. "Prediction of Parking Space Availability Using Improved MAT-LSTM Network". ISPRS International Journal of Geo-Information 13, n. 5 (1 maggio 2024): 151. http://dx.doi.org/10.3390/ijgi13050151.
Alaameri, Zahra Hasan Oleiwi, e Mustafa Abdulsahib Faihan. "Forecasting the Accounting Profits of the Banks Listed in Iraq Stock Exchange Using Artificial Neural Networks". Webology 19, n. 1 (20 gennaio 2022): 2669–82. http://dx.doi.org/10.14704/web/v19i1/web19177.
Moskalenko, Valentyna, Anastasija Santalova e Nataliia Fonta. "STUDY OF NEURAL NETWORKS FOR FORECASTING THE VALUE OF COMPANY SHARES IN AN UNSTABLE ECONOMY". Bulletin of National Technical University "KhPI". Series: System Analysis, Control and Information Technologies, n. 2 (8) (23 dicembre 2022): 16–23. http://dx.doi.org/10.20998/2079-0023.2022.02.03.
Liu, Chen. "Prediction and Analysis of Artwork Price Based on Deep Neural Network". Scientific Programming 2022 (10 marzo 2022): 1–10. http://dx.doi.org/10.1155/2022/7133910.
Lee, Jaekyung, Hyunwoo Kim e Hyungkyoo Kim. "Commercial Vacancy Prediction Using LSTM Neural Networks". Sustainability 13, n. 10 (12 maggio 2021): 5400. http://dx.doi.org/10.3390/su13105400.
Khalil, Kasem, Omar Eldash, Ashok Kumar e Magdy Bayoumi. "Economic LSTM Approach for Recurrent Neural Networks". IEEE Transactions on Circuits and Systems II: Express Briefs 66, n. 11 (novembre 2019): 1885–89. http://dx.doi.org/10.1109/tcsii.2019.2924663.
Ergen, Tolga, e Suleyman Serdar Kozat. "Unsupervised Anomaly Detection With LSTM Neural Networks". IEEE Transactions on Neural Networks and Learning Systems 31, n. 8 (agosto 2020): 3127–41. http://dx.doi.org/10.1109/tnnls.2019.2935975.
Wei, Xiaolu, Binbin Lei, Hongbing Ouyang e Qiufeng Wu. "Stock Index Prices Prediction via Temporal Pattern Attention and Long-Short-Term Memory". Advances in Multimedia 2020 (10 dicembre 2020): 1–7. http://dx.doi.org/10.1155/2020/8831893.
Wei, Chih-Chiang. "Comparison of River Basin Water Level Forecasting Methods: Sequential Neural Networks and Multiple-Input Functional Neural Networks". Remote Sensing 12, n. 24 (20 dicembre 2020): 4172. http://dx.doi.org/10.3390/rs12244172.
Han, Shipeng, Zhen Meng, Xingcheng Zhang e Yuepeng Yan. "Hybrid Deep Recurrent Neural Networks for Noise Reduction of MEMS-IMU with Static and Dynamic Conditions". Micromachines 12, n. 2 (20 febbraio 2021): 214. http://dx.doi.org/10.3390/mi12020214.
Wang, Qinghua, Yuexiao Yu, Hosameldin O. A. Ahmed, Mohamed Darwish e Asoke K. Nandi. "Open-Circuit Fault Detection and Classification of Modular Multilevel Converters in High Voltage Direct Current Systems (MMC-HVDC) with Long Short-Term Memory (LSTM) Method". Sensors 21, n. 12 (17 giugno 2021): 4159. http://dx.doi.org/10.3390/s21124159.
Victor, Nancy, e Daphne Lopez. "sl-LSTM". International Journal of Grid and High Performance Computing 12, n. 3 (luglio 2020): 1–16. http://dx.doi.org/10.4018/ijghpc.2020070101.
Kłosowski, Grzegorz, Anna Hoła, Tomasz Rymarczyk, Mariusz Mazurek, Konrad Niderla e Magdalena Rzemieniak. "Using Machine Learning in Electrical Tomography for Building Energy Efficiency through Moisture Detection". Energies 16, n. 4 (11 febbraio 2023): 1818. http://dx.doi.org/10.3390/en16041818.
Ayyildiz, Ertugrul, e Melike Erdoğan. "Forecasting of daily dam occupancy rates using LSTM networks". World Journal of Environmental Research 12, n. 1 (31 maggio 2022): 33–42. http://dx.doi.org/10.18844/wjer.v12i1.7732.
You, Yue, Woo-Hyoung Kim e Yong-Seok Cho. "Stock Market Prediction Based on LSTM Neural Networks". Korea International Trade Research Institute 19, n. 2 (30 aprile 2023): 391–407. http://dx.doi.org/10.16980/jitc.19.2.202304.391.
Zhou, Lixia, Xia Chen, Runsha Dong e Shan Yang. "Hotspots Prediction Based on LSTM Neural Network for Cellular Networks". Journal of Physics: Conference Series 1624 (ottobre 2020): 052016. http://dx.doi.org/10.1088/1742-6596/1624/5/052016.
Wang, Geng, Xuemin Yao, Jianjun Cui, Yonggang Yan, Jun Dai e Wu Zhao. "A novel piezoelectric hysteresis modeling method combining LSTM and NARX neural networks". Modern Physics Letters B 34, n. 28 (16 giugno 2020): 2050306. http://dx.doi.org/10.1142/s0217984920503066.
Shewalkar, Apeksha, Deepika Nyavanandi e Simone A. Ludwig. "Performance Evaluation of Deep Neural Networks Applied to Speech Recognition: RNN, LSTM and GRU". Journal of Artificial Intelligence and Soft Computing Research 9, n. 4 (1 ottobre 2019): 235–45. http://dx.doi.org/10.2478/jaiscr-2019-0006.
Yadav, Omprakash, Rachael Dsouza, Rhea Dsouza e Janice Jose. "Soccer Action video Classification using Deep Learning". International Journal for Research in Applied Science and Engineering Technology 10, n. 6 (30 giugno 2022): 1060–63. http://dx.doi.org/10.22214/ijraset.2022.43929.