Cash flow prediction: MLP and LSTM compared to ARIMA and Prophet
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DOI: 10.1007/s10660-019-09362-7
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References listed on IDEAS
- Qian Wang & Jijun Yu & Weiwei Deng, 2019. "An adjustable re-ranking approach for improving the individual and aggregate diversities of product recommendations," Electronic Commerce Research, Springer, vol. 19(1), pages 59-79, March.
- Ke Gong & Yi Peng & Yong Wang & Maozeng Xu, 2018. "Time series analysis for C2C conversion rate," Electronic Commerce Research, Springer, vol. 18(4), pages 763-789, December.
- Shasha Liu & Bingjia Shao & Yuan Gao & Su Hu & Yi Li & Weigui Zhou, 2018. "Game theoretic approach of a novel decision policy for customers based on big data," Electronic Commerce Research, Springer, vol. 18(2), pages 225-240, June.
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Cited by:
- Zhang, Junting & Liu, Haifei & Bai, Wei & Li, Xiaojing, 2024. "A hybrid approach of wavelet transform, ARIMA and LSTM model for the share price index futures forecasting," The North American Journal of Economics and Finance, Elsevier, vol. 69(PB).
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Keywords
Cash flow prediction; Accounts receivable; Neural networks; LSTM; MLP; ARIMA; Prophet;All these keywords.
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