نتائج البحث

In-Depth Insights into the Application of Recurrent Neural Networks (RNNs) in Traffic Prediction: A Comprehensive Review.

• Authors : He, Yuxin¹ (AUTHOR) ; Huang, Ping¹ (AUTHOR) ; Hong, Weihang¹ (AUTHOR)

• Source: Algorithms. Sep2024, Vol. 17 Issue 9, p398. 43p.

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Deep learning–based long short-term memory recurrent neural networks for monthly rainfall forecasting in Ghana, West Africa.

• Authors : Dotse, Sam-Quarcoo¹ (AUTHOR)

• Source: Theoretical & Applied Climatology. Apr2024, Vol. 155 Issue 4, p3033-3045. 13p.

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A Combined Model Based on Recurrent Neural Networks and Graph Convolutional Networks for Financial Time Series Forecasting.

• Authors : Lazcano, Ana^1,2 (AUTHOR) ; Herrera, Pedro Javier¹ (AUTHOR); Monge, Manuel² (AUTHOR)

• Source: Mathematics (2227-7390). Jan2023, Vol. 11 Issue 1, p224. 21p.

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Transfer-recursive-ensemble learning for multi-day COVID-19 prediction in India using recurrent neural networks.

• Authors : Chakraborty, Debasrita¹ (AUTHOR); Goswami, Debayan² (AUTHOR); Ghosh, Susmita² (AUTHOR)

• Source: Scientific Reports. 4/26/2023, Vol. 13 Issue 1, p1-12. 12p.

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SAM-Net: Spatio-Temporal Sequence Typhoon Cloud Image Prediction Net with Self-Attention Memory.

• Authors : Ren, Yanzhao¹ (AUTHOR) ; Ye, Jinyuan¹ (AUTHOR) ; Wang, Xiaochuan¹ (AUTHOR)

• Source: Remote Sensing. Nov2024, Vol. 16 Issue 22, p4213. 20p.

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Synergistic sunspot forecasting: a fusion of time series analysis and machine learning.

• Authors : Chen, Menghui¹ (AUTHOR); Kumarasamy, Suresh^2,3 (AUTHOR); Srinivasan, Sabarathinam¹ (AUTHOR)

• Source: Pramana: Journal of Physics. Mar2025, Vol. 99 Issue 1, p1-14. 14p.

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Forecasting the elasticity of variance with LSTM recurrent neural networks.

• Authors : Kim, Hyun-Gyoon¹ (AUTHOR); Kim, Jeong-Hoon¹ (AUTHOR)

• Source: International Journal of Computer Mathematics. Jan2023, Vol. 100 Issue 1, p209-218. 10p.

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Improving daily reference evapotranspiration forecasts: Designing AI-enabled recurrent neural networks based long short-term memory

• Authors : Mumtaz Ali; Jesu Vedha Nayahi; Erfan Abdi

Subjects: Agriculture; Deep learning; ETo

• Source: Ecological Informatics, Vol 85, Iss , Pp 102995- (2025)

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Research on Impulse Power Load Forecasting Based on Improved Recurrent Neural Networks.

• Authors : Feng, Chenyang¹ (AUTHOR); Xu, Kang¹ (AUTHOR); Ma, Haoyun¹ (AUTHOR)

• Source: Computational Intelligence & Neuroscience. 4/23/2022, p1-9. 9p.

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Recurrent neural networks for conflict forecasting.

• Authors : Malone, Iris¹ (AUTHOR)

• Source: International Interactions. Jul/Aug2022, Vol. 48 Issue 4, p614-632. 19p.

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