These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
155 related articles for article (PubMed ID: 34778753)
41. Intraday seasonalities and nonstationarity of trading volume in financial markets: Collective features. Graczyk MB; Duarte Queirós SM PLoS One; 2017; 12(7):e0179198. PubMed ID: 28753676 [TBL] [Abstract][Full Text] [Related]
42. Biclustering Learning of Trading Rules. Huang Q; Wang T; Tao D; Li X IEEE Trans Cybern; 2015 Oct; 45(10):2287-98. PubMed ID: 25494520 [TBL] [Abstract][Full Text] [Related]
43. Reinforced Labels: Multi-Agent Deep Reinforcement Learning for Point-Feature Label Placement. Bobak P; Cmolik L; Cadik M IEEE Trans Vis Comput Graph; 2023 Sep; PP():. PubMed ID: 37695975 [TBL] [Abstract][Full Text] [Related]
44. Identification of Insider Trading in the Securities Market Based on Multi-task Deep Neural Network. Li G; Li Z; Wang Z; Zhang K Comput Intell Neurosci; 2022; 2022():4874516. PubMed ID: 35498190 [TBL] [Abstract][Full Text] [Related]
45. Empirical mode decomposition using deep learning model for financial market forecasting. Jin Z; Jin Y; Chen Z PeerJ Comput Sci; 2022; 8():e1076. PubMed ID: 36262133 [TBL] [Abstract][Full Text] [Related]
46. Performance of technical trading rules: evidence from Southeast Asian stock markets. Tharavanij P; Siraprapasiri V; Rajchamaha K Springerplus; 2015; 4():552. PubMed ID: 26435898 [TBL] [Abstract][Full Text] [Related]
47. Analyzing the Importance of Broker Identities in the Limit Order Book Through Deep Learning. Choi SP; Chan YH; Lam SS; Hung HY Big Data; 2021 Apr; 9(2):89-99. PubMed ID: 33202194 [TBL] [Abstract][Full Text] [Related]
48. IHG-MA: Inductive heterogeneous graph multi-agent reinforcement learning for multi-intersection traffic signal control. Yang S; Yang B; Kang Z; Deng L Neural Netw; 2021 Jul; 139():265-277. PubMed ID: 33838602 [TBL] [Abstract][Full Text] [Related]
49. Quantum reinforcement learning. Dong D; Chen C; Li H; Tarn TJ IEEE Trans Syst Man Cybern B Cybern; 2008 Oct; 38(5):1207-20. PubMed ID: 18784007 [TBL] [Abstract][Full Text] [Related]
51. Biased Pressure: Cyclic Reinforcement Learning Model for Intelligent Traffic Signal Control. Ibrokhimov B; Kim YJ; Kang S Sensors (Basel); 2022 Apr; 22(7):. PubMed ID: 35408431 [TBL] [Abstract][Full Text] [Related]
52. Intraday return predictability: Evidence from commodity ETFs and their related volatility indices. Xu Y; Bouri E; Saeed T; Wen Z Resour Policy; 2020 Dec; 69():101830. PubMed ID: 34173420 [TBL] [Abstract][Full Text] [Related]
53. An econometric model for intraday electricity trading. Kremer M; Kiesel R; Paraschiv F Philos Trans A Math Phys Eng Sci; 2021 Jul; 379(2202):20190624. PubMed ID: 34092107 [TBL] [Abstract][Full Text] [Related]
54. Exploration With Task Information for Meta Reinforcement Learning. Jiang P; Song S; Huang G IEEE Trans Neural Netw Learn Syst; 2023 Aug; 34(8):4033-4046. PubMed ID: 34739382 [TBL] [Abstract][Full Text] [Related]
55. Scalable Scheduling of Semiconductor Packaging Facilities Using Deep Reinforcement Learning. Park IB; Park J IEEE Trans Cybern; 2023 Jun; 53(6):3518-3531. PubMed ID: 34860658 [TBL] [Abstract][Full Text] [Related]
56. Safe reinforcement learning under temporal logic with reward design and quantum action selection. Cai M; Xiao S; Li J; Kan Z Sci Rep; 2023 Feb; 13(1):1925. PubMed ID: 36732441 [TBL] [Abstract][Full Text] [Related]
57. Probing relationships between reinforcement learning and simple behavioral strategies to understand probabilistic reward learning. Iyer ES; Kairiss MA; Liu A; Otto AR; Bagot RC J Neurosci Methods; 2020 Jul; 341():108777. PubMed ID: 32417532 [TBL] [Abstract][Full Text] [Related]
58. Dynamic Adjustment Model of the Water Rights Trading Price Based on Water Resource Scarcity Value Analysis. Wu XY; Wu FP; Li F; Xu X Int J Environ Res Public Health; 2021 Feb; 18(5):. PubMed ID: 33669014 [TBL] [Abstract][Full Text] [Related]