Search Results - subject:"Recurrent neural network"

Modeling behavioral dynamics in digital content consumption : an attention-based neural point process approach with applications in video games

Yin, Junming; Feng, Yue; Liu, Yong - In: Marketing science 44 (2025) 1, pp. 220-239

Persistent link: https://www.econbiz.de/10015197252

Volatility forecasting of clean energy ETF using GARCH-MIDAS with neural network model

Zhang, Li; Wang, Lu; Thong Trung Nguyen; Ren, Ruiyi - In: Finance research letters 70 (2024), pp. 1-13

Persistent link: https://www.econbiz.de/10015193018

Deep learning-based genetic algorithm for the robust hub allocation problem with discrete scenarios

Berrajaa, Achraf - In: International journal of logistics systems and … 48 (2024) 4, pp. 489-507

Persistent link: https://www.econbiz.de/10015065804

Effective crude oil prediction using CHS-EMD decomposition and PS-RNN model

Usha Ruby, A.; Chaithanya, B. N.; Patil, Renuka - In: Computational economics 64 (2024) 2, pp. 1295-1314

Persistent link: https://www.econbiz.de/10015078090

Hierarchical RNN-based framework for throughput prediction in automotive production systems

Chen, Mengfei; Furness, Richard; Gupta, Rajesh; … - In: International journal of production research 62 (2024) 5, pp. 1699-1714

Persistent link: https://www.econbiz.de/10014546268

Seaport profit analysis and efficient management strategies under stochastic disruptions

Truong Ngoc Cuong; Kim, Hwan-Seong; Le Ngoc Bao Long; … - In: Maritime economics & logistics 26 (2024) 2, pp. 212-240

Persistent link: https://www.econbiz.de/10014557754

Harnessing attention-based graph recurrent neural networks for enhanced conversational flow prediction via conversational graph construction

Sujatha, R.; Nimala, K. - In: Journal of information & knowledge management : JIKM 23 (2024) 3, pp. 1-17

Persistent link: https://www.econbiz.de/10014575784

A novel neural network architecture and cross-model transfer learning for multi-task autonomous driving

Li, Youwei; Qu, Jian - In: Data Technologies and Applications 58 (2024) 5, pp. 693-717

Purpose The purpose of this research is to achieve multi-task autonomous driving by adjusting the network architecture of the model. Meanwhile, after achieving multi-task autonomous driving, the authors found that the trained neural network model performs poorly in untrained scenarios....

Persistent link: https://www.econbiz.de/10015342715

Bitcoin return volatility forecasting: A comparative study between GARCH and RNN

Shen, Ze; Wan, Qing; Leatham, David J. - In: Journal of Risk and Financial Management 14 (2021) 7, pp. 1-18

One of the notable features of bitcoin is its extreme volatility. The modeling and forecasting of bitcoin volatility are crucial for bitcoin investors' decision-making analysis and risk management. However, most previous studies of bitcoin volatility were founded on econometric models. Research...

Persistent link: https://www.econbiz.de/10013201021

Bitcoin return volatility forecasting : a comparative study between GARCH and RNN

Shen, Ze; Wan, Qing; Leatham, David J. - In: Journal of risk and financial management : JRFM 14 (2021) 7, pp. 1-18

One of the notable features of bitcoin is its extreme volatility. The modeling and forecasting of bitcoin volatility are crucial for bitcoin investors’ decision-making analysis and risk management. However, most previous studies of bitcoin volatility were founded on econometric models....

Persistent link: https://www.econbiz.de/10012626254