The main difference between stochastic models and deterministic models lies in the level of uncertainty and randomness considered in their input and output variables.
In a deterministic model, every input variable has a fixed and known value, and the output is completely predictable based on those inputs. In other words, the relationship between inputs and outputs is completely determined with no randomness involved. Deterministic models are typically used when the system being modeled can be accurately and precisely described.
On the other hand, stochastic models incorporate randomness and uncertainty into the input variables and allow for a range of possible outcomes or states in the output variables. Stochastic models make use of probability distributions to represent the uncertainty in the inputs and calculate the probability of different outcomes in the outputs. These models are used when there are numerous factors that contribute to the outcome and their exact values are not known or cannot be precisely determined.
In summary, deterministic models assume that inputs and outputs are fixed and predictable, while stochastic models account for random variations and uncertainty in both inputs and outputs.
different between stochastic model and deterministic model
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