Prediction model of thermal environment dissatisfaction rate based on Bayesian theory

Thermal environmental comfort is one of the important contents of environmental health, and the thermal environmental prediction satisfaction rate is an important index for thermal comfort evaluation. Through the pre-measured environmental and human body parameters, forms a priori distribution of the dissatisfaction rate of thermal environment prediction by PMV-PPD model. Combined with the results of field investigation of dissatisfaction rate, calculates the posterior distribution of dissatisfaction rate using Bayesian formula and Markov chain Monte Carlo method. The results of numerical examples demonstrate the effectiveness of the method. The study shows that the variance of dissatisfied priori distribution and the number of survey samples affect the prediction results. With the number of samples increasing, the influence of priori distribution on the prediction results gradually decreases. Considering the action of subjective and objective factors, the model is suitable for the design and analysis of building thermal environment.