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For: Fernández C, Salinas L, Torres CE. A meta extreme learning machine method for forecasting financial time series. APPL INTELL 2019;49:532-54. [DOI: 10.1007/s10489-018-1282-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
Number Cited by Other Article(s)
1
Time Series Reconstruction and Classification: A Comprehensive Comparative Study. APPL INTELL 2022. [DOI: 10.1007/s10489-021-02926-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
2
Zhang H, Hu B, Wang X, Xu J, Wang L, Sun Q, Wang Z. Self-organizing deep belief modular echo state network for time series prediction. Knowl Based Syst 2021. [DOI: 10.1016/j.knosys.2021.107007] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
3
Anand G, Nayak R. DeLTa: Deep local pattern representation for time-series clustering and classification using visual perception. Knowl Based Syst 2021. [DOI: 10.1016/j.knosys.2020.106551] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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