Neural network modeling of the differential expansion of a 200 MWsteam turbine

摘要

A new neural network approach is applied to the modeling of thedifferential expansion of a 200 MW steam turbine. This approach uses BPnetwork with internal lags and is useful for modeling the process inwhich outputs change slowly with inputs