Journal articles on the topic 'LSTM Neural networks'
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Bakir, Houda, Ghassen Chniti, and Hédi Zaher. "E-Commerce Price Forecasting Using LSTM Neural Networks." International Journal of Machine Learning and Computing 8, no. 2 (April 2018): 169–74. http://dx.doi.org/10.18178/ijmlc.2018.8.2.682.
Yu, Yong, Xiaosheng Si, Changhua Hu, and Jianxun Zhang. "A Review of Recurrent Neural Networks: LSTM Cells and Network Architectures." Neural Computation 31, no. 7 (July 2019): 1235–70. http://dx.doi.org/10.1162/neco_a_01199.
Kalinin, Maxim, Vasiliy Krundyshev, and 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, and Weixin Sun. "Research on SOC Estimation Method for Lithium-Ion Batteries Based on Neural Network." World Electric Vehicle Journal 14, no. 10 (October 2, 2023): 275. http://dx.doi.org/10.3390/wevj14100275.
Sridhar, C., and Aniruddha Kanhe. "Performance Comparison of Various Neural Networks for Speech Recognition." Journal of Physics: Conference Series 2466, no. 1 (March 1, 2023): 012008. http://dx.doi.org/10.1088/1742-6596/2466/1/012008.
Wan, Yingliang, Hong Tao, and Li Ma. "Forecasting Zhejiang Province's GDP Using a CNN-LSTM Model." Frontiers in Business, Economics and Management 13, no. 3 (March 5, 2024): 233–35. http://dx.doi.org/10.54097/bmq2dy63.
Liu, David, and An Wei. "Regulated LSTM Artificial Neural Networks for Option Risks." FinTech 1, no. 2 (June 2, 2022): 180–90. http://dx.doi.org/10.3390/fintech1020014.
Pal, Subarno, Soumadip Ghosh, and Amitava Nag. "Sentiment Analysis in the Light of LSTM Recurrent Neural Networks." International Journal of Synthetic Emotions 9, no. 1 (January 2018): 33–39. http://dx.doi.org/10.4018/ijse.2018010103.
Kabildjanov, A. S., Ch Z. Okhunboboeva, and 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, no. 1 (June 1, 2023): 012015. http://dx.doi.org/10.1088/1755-1315/1206/1/012015.
Yu, Dian, and Shouqian Sun. "A Systematic Exploration of Deep Neural Networks for EDA-Based Emotion Recognition." Information 11, no. 4 (April 15, 2020): 212. http://dx.doi.org/10.3390/info11040212.
Zhang, Chun-Xiang, Shu-Yang Pang, Xue-Yao Gao, Jia-Qi Lu, and Bo Yu. "Attention Neural Network for Biomedical Word Sense Disambiguation." Discrete Dynamics in Nature and Society 2022 (January 10, 2022): 1–14. http://dx.doi.org/10.1155/2022/6182058.
Mao, Congmin, and 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, no. 3 (May 20, 2024): 679–84. http://dx.doi.org/10.20965/jaciii.2024.p0679.
Mountzouris, Konstantinos, Isidoros Perikos, and Ioannis Hatzilygeroudis. "Speech Emotion Recognition Using Convolutional Neural Networks with Attention Mechanism." Electronics 12, no. 20 (October 23, 2023): 4376. http://dx.doi.org/10.3390/electronics12204376.
Wan, Huaiyu, Shengnan Guo, Kang Yin, Xiaohui Liang, and Youfang Lin. "CTS-LSTM: LSTM-based neural networks for correlatedtime series prediction." Knowledge-Based Systems 191 (March 2020): 105239. http://dx.doi.org/10.1016/j.knosys.2019.105239.
Xu, Lingfeng, Xiang Chen, Shuai Cao, Xu Zhang, and Xun Chen. "Feasibility Study of Advanced Neural Networks Applied to sEMG-Based Force Estimation." Sensors 18, no. 10 (September 25, 2018): 3226. http://dx.doi.org/10.3390/s18103226.
Blinov, I., V. Miroshnyk, and V. Sychova. "Short-term forecasting of electricity imbalances using artificial neural networks." IOP Conference Series: Earth and Environmental Science 1254, no. 1 (October 1, 2023): 012029. http://dx.doi.org/10.1088/1755-1315/1254/1/012029.
Pavlatos, Christos, Evangelos Makris, Georgios Fotis, Vasiliki Vita, and Valeri Mladenov. "Enhancing Electrical Load Prediction Using a Bidirectional LSTM Neural Network." Electronics 12, no. 22 (November 15, 2023): 4652. http://dx.doi.org/10.3390/electronics12224652.
Song, Dazhi, and Dazhi Song. "Stock Price Prediction based on Time Series Model and Long Short-term Memory Method." Highlights in Business, Economics and Management 24 (January 22, 2024): 1203–10. http://dx.doi.org/10.54097/e75xgk49.
Gers, Felix A., Jürgen Schmidhuber, and Fred Cummins. "Learning to Forget: Continual Prediction with LSTM." Neural Computation 12, no. 10 (October 1, 2000): 2451–71. http://dx.doi.org/10.1162/089976600300015015.
Wei, Jun, Fan Yang, Xiao-Chen Ren, and Silin Zou. "A Short-Term Prediction Model of PM2.5 Concentration Based on Deep Learning and Mode Decomposition Methods." Applied Sciences 11, no. 15 (July 27, 2021): 6915. http://dx.doi.org/10.3390/app11156915.
Bucci, Andrea. "Realized Volatility Forecasting with Neural Networks." Journal of Financial Econometrics 18, no. 3 (2020): 502–31. http://dx.doi.org/10.1093/jjfinec/nbaa008.
Du, Shaohui, Zhenghan Chen, Haoyan Wu, Yihong Tang, and YuanQing Li. "Image Recommendation Algorithm Combined with Deep Neural Network Designed for Social Networks." Complexity 2021 (July 2, 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, and Mohammad Aman Ullah. "Evolving Long Short-Term Memory Network-Based Text Classification." Computational Intelligence and Neuroscience 2022 (February 21, 2022): 1–11. http://dx.doi.org/10.1155/2022/4725639.
Zhang, Cheng, Luying Li, Yanmei Liu, Xuejiao Luo, Shangguan Song, and 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, and Sebastián Ventura. "Unemployment Rate Prediction Using a Hybrid Model of Recurrent Neural Networks and Genetic Algorithms." Applied Sciences 14, no. 8 (April 10, 2024): 3174. http://dx.doi.org/10.3390/app14083174.
Chuang, Chia-Chun, Chien-Ching Lee, Chia-Hong Yeng, Edmund-Cheung So, and Yeou-Jiunn Chen. "Attention Mechanism-Based Convolutional Long Short-Term Memory Neural Networks to Electrocardiogram-Based Blood Pressure Estimation." Applied Sciences 11, no. 24 (December 17, 2021): 12019. http://dx.doi.org/10.3390/app112412019.
Tra, Nguyen Ngoc, Ho Phuoc Tien, Nguyen Thanh Dat, and 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, no. 12.2 (December 9, 2019): 61. http://dx.doi.org/10.31130/ict-ud.2019.94.
Nguyen, Viet-Hung, Minh-Tuan Nguyen, Jeongsik Choi, and Yong-Hwa Kim. "NLOS Identification in WLANs Using Deep LSTM with CNN Features." Sensors 18, no. 11 (November 20, 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, and 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, no. 9 (April 19, 2022): 1318. http://dx.doi.org/10.3390/w14091318.
Liu, Lunhaojie, Wen Fu, Xingao Bian, and Juntao Fei. "Adaptive Intelligent Sliding Mode Control of a Dynamic System with a Long Short-Term Memory Structure." Mathematics 10, no. 7 (April 6, 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, no. 1 (March 30, 2024): 78–88. http://dx.doi.org/10.17150/2713-1734.2024.6(1).78-88.
Zhang, Feizhou, Ke Shang, Lei Yan, Haijing Nan, and Zicong Miao. "Prediction of Parking Space Availability Using Improved MAT-LSTM Network." ISPRS International Journal of Geo-Information 13, no. 5 (May 1, 2024): 151. http://dx.doi.org/10.3390/ijgi13050151.
Alaameri, Zahra Hasan Oleiwi, and Mustafa Abdulsahib Faihan. "Forecasting the Accounting Profits of the Banks Listed in Iraq Stock Exchange Using Artificial Neural Networks." Webology 19, no. 1 (January 20, 2022): 2669–82. http://dx.doi.org/10.14704/web/v19i1/web19177.
Moskalenko, Valentyna, Anastasija Santalova, and 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, no. 2 (8) (December 23, 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 (March 10, 2022): 1–10. http://dx.doi.org/10.1155/2022/7133910.
Lee, Jaekyung, Hyunwoo Kim, and Hyungkyoo Kim. "Commercial Vacancy Prediction Using LSTM Neural Networks." Sustainability 13, no. 10 (May 12, 2021): 5400. http://dx.doi.org/10.3390/su13105400.
Khalil, Kasem, Omar Eldash, Ashok Kumar, and Magdy Bayoumi. "Economic LSTM Approach for Recurrent Neural Networks." IEEE Transactions on Circuits and Systems II: Express Briefs 66, no. 11 (November 2019): 1885–89. http://dx.doi.org/10.1109/tcsii.2019.2924663.
Ergen, Tolga, and Suleyman Serdar Kozat. "Unsupervised Anomaly Detection With LSTM Neural Networks." IEEE Transactions on Neural Networks and Learning Systems 31, no. 8 (August 2020): 3127–41. http://dx.doi.org/10.1109/tnnls.2019.2935975.
Wei, Xiaolu, Binbin Lei, Hongbing Ouyang, and Qiufeng Wu. "Stock Index Prices Prediction via Temporal Pattern Attention and Long-Short-Term Memory." Advances in Multimedia 2020 (December 10, 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, no. 24 (December 20, 2020): 4172. http://dx.doi.org/10.3390/rs12244172.
Han, Shipeng, Zhen Meng, Xingcheng Zhang, and Yuepeng Yan. "Hybrid Deep Recurrent Neural Networks for Noise Reduction of MEMS-IMU with Static and Dynamic Conditions." Micromachines 12, no. 2 (February 20, 2021): 214. http://dx.doi.org/10.3390/mi12020214.
Wang, Qinghua, Yuexiao Yu, Hosameldin O. A. Ahmed, Mohamed Darwish, and 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, no. 12 (June 17, 2021): 4159. http://dx.doi.org/10.3390/s21124159.
Victor, Nancy, and Daphne Lopez. "sl-LSTM." International Journal of Grid and High Performance Computing 12, no. 3 (July 2020): 1–16. http://dx.doi.org/10.4018/ijghpc.2020070101.
Kłosowski, Grzegorz, Anna Hoła, Tomasz Rymarczyk, Mariusz Mazurek, Konrad Niderla, and Magdalena Rzemieniak. "Using Machine Learning in Electrical Tomography for Building Energy Efficiency through Moisture Detection." Energies 16, no. 4 (February 11, 2023): 1818. http://dx.doi.org/10.3390/en16041818.
Ayyildiz, Ertugrul, and Melike Erdoğan. "Forecasting of daily dam occupancy rates using LSTM networks." World Journal of Environmental Research 12, no. 1 (May 31, 2022): 33–42. http://dx.doi.org/10.18844/wjer.v12i1.7732.
You, Yue, Woo-Hyoung Kim, and Yong-Seok Cho. "Stock Market Prediction Based on LSTM Neural Networks." Korea International Trade Research Institute 19, no. 2 (April 30, 2023): 391–407. http://dx.doi.org/10.16980/jitc.19.2.202304.391.
Zhou, Lixia, Xia Chen, Runsha Dong, and Shan Yang. "Hotspots Prediction Based on LSTM Neural Network for Cellular Networks." Journal of Physics: Conference Series 1624 (October 2020): 052016. http://dx.doi.org/10.1088/1742-6596/1624/5/052016.
Wang, Geng, Xuemin Yao, Jianjun Cui, Yonggang Yan, Jun Dai, and Wu Zhao. "A novel piezoelectric hysteresis modeling method combining LSTM and NARX neural networks." Modern Physics Letters B 34, no. 28 (June 16, 2020): 2050306. http://dx.doi.org/10.1142/s0217984920503066.
Shewalkar, Apeksha, Deepika Nyavanandi, and 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, no. 4 (October 1, 2019): 235–45. http://dx.doi.org/10.2478/jaiscr-2019-0006.
Yadav, Omprakash, Rachael Dsouza, Rhea Dsouza, and Janice Jose. "Soccer Action video Classification using Deep Learning." International Journal for Research in Applied Science and Engineering Technology 10, no. 6 (June 30, 2022): 1060–63. http://dx.doi.org/10.22214/ijraset.2022.43929.