4 April 1997 High-order polytomous Boltzmann machine and forecasting time series I
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Abstract
We use the polytomous Boltzmann Machine for time series forecasting and prediction applications. We will simulate the polytomous Boltzmann Machine by using the binary Boltzmann Machine. We will show our software (1) can learn and predict the behavior of deterministic dynamic systems. Given enough training, the software can predict with 100% accuracy; (2) can learn and predict the behavior of the Markov chains (or probabilistic finite state machines). Given enough training, the software can predict with 100% accuracy.
© (1997) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ying Liu, "High-order polytomous Boltzmann machine and forecasting time series I", Proc. SPIE 3077, Applications and Science of Artificial Neural Networks III, (4 April 1997); doi: 10.1117/12.271502; https://doi.org/10.1117/12.271502
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