IKBFU researchers have developed an artificial intelligence (AI) model that can predict the behavior of complex stochastic systems such as financial markets and traffic flows. This model was trained on a computer simulation of a biological neuron exposed to noise, making it capable of generalizing and identifying new patterns.
Alexander Khramov, head of the research, states that the model was able to predict the physical effect of stochastic resonance, which had not been taken into account before. This means that at a given noise intensity the chaotic behavior of a neuron becomes more orderly, which is important for understanding complex systems.
This breakthrough opens new horizons for the use of artificial intelligence models in various fields, from economics to urban traffic management. Models that can deal with noise can be useful in predicting the behavior of systems under uncertainty and random effects, which can help make more accurate decisions.
Source: Ferra
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