The extreme learning machine usually exist the problems on high-dimensional data modeling in chemical process.Aiming at solving these problems

the auto-associative neural network is combined

in which the auto-associative neural network is constructed to filter redundant information and extract characteristic components

and these characteristic components are trained by extreme learning machine.Thus

a data feature extraction based auto-associative neural network-extreme learning machine(AANN-ELM)is formed.Meanwhile

the effectiveness of this network is verified by the UCI standard data sets and the purified terephthalic acid(PTA)solvent system.The result indicates that AANN-ELM has the characteristics of fast learning speed

stable network output

and high model precision in handling with high-dimensional data

which will provide a new way to apply the neural network in complex chemical production.