Hierarchical Bayesian neural nets for air-conditioning load prediction: nonlinear dynamics approach

Given time series data, model dynamical systems are built using a hierarchical Bayesian scheme with feedforward neural nets and then the models are compared in terms of marginal likelihood. The model with the highest marginal likelihood is used for predictions. The algorithm is applied to building air-conditioning load prediction.