<P> It is possible that economic models can also be improved through an application of chaos theory, but predicting the health of an economic system and what factors influence it most is an extremely complex task . Economic and financial systems are fundamentally different from those in the classical natural sciences since the former are inherently stochastic in nature, as they result from the interactions of people, and thus pure deterministic models are unlikely to provide accurate representations of the data . The empirical literature that tests for chaos in economics and finance presents very mixed results, in part due to confusion between specific tests for chaos and more general tests for non-linear relationships . </P> <P> Traffic forecasting may benefit from applications of chaos theory . Better predictions of when traffic will occur would allow measures to be taken to disperse it before it would have occurred . Combining chaos theory principles with a few other methods has led to a more accurate short - term prediction model (see the plot of the BML traffic model at right). </P> <P> Chaos theory has been applied to environmental water cycle data (aka hydrological data), such as rainfall and streamflow . These studies have yielded controversial results, because the methods for detecting a chaotic signature are often relatively subjective . Early studies tended to "succeed" in finding chaos, whereas subsequent studies and meta - analyses called those studies into question and provided explanations for why these datasets are not likely to have low - dimension chaotic dynamics . </P>

State one uncertainty in the computer model that limits