Dynamic uncertainty evaluation method for cold chain temperature parameters

The invention provides an uncertainty dynamic evaluation method for a cold chain temperature parameter. Comprising the following steps: sampling the temperature of a detected refrigeration house or cold chain vehicle; determining a distribution type of a prior distribution and likelihood function and a probability density function expression; calculating a joint probability density function expression proportional to posteriori distribution according to a Bayesian formula; setting suggestion distribution which is easy to sample and has mutually independent sampling results, and constructing a probability density function expression of the suggestion distribution; determining a transfer density function by using a joint probability density function in direct proportion to posterior distribution and suggested distribution, and determining a transfer rule; obtaining a sample according to the transfer density function and the transfer rule, and evaluating the uncertainty of the temperature measurement by using a