Improved Demand Forecasting Using Local Models Based on Delay Time Embedding
暂无分享，去创建一个
[1] Marco Taisch,et al. Neural networks in production planning and control , 1999 .
[2] S. Hohmann. The Bullwhip Effect in Supply Chains , 2014 .
[3] Toshimitsu Ushio,et al. Controlling chaos in a switched arrival system , 1995 .
[4] D. Ruelle,et al. Recurrence Plots of Dynamical Systems , 1987 .
[5] George Sugihara,et al. Nonlinear forecasting for the classification of natural time series , 1994, Philosophical Transactions of the Royal Society of London. Series A: Physical and Engineering Sciences.
[6] Thomas Ragg,et al. Bayesian learning for sales rate prediction for thousands of retailers , 2002, Neurocomputing.
[7] H. Abarbanel,et al. Determining embedding dimension for phase-space reconstruction using a geometrical construction. , 1992, Physical review. A, Atomic, molecular, and optical physics.
[8] J. Zbilut,et al. Embeddings and delays as derived from quantification of recurrence plots , 1992 .
[9] Bernd Scholz-Reiter,et al. Entropy as a Measurement for the Quality of Demand Forecasting , 2007 .