A SIA-LSTM based virtual metrology for quality variables in irregular sampled time sequence of industrial processes

•An SIA-LSTM is developed for quality variables in irregular sampled time sequence.•An attention neural network is first designed to adaptively learn the dynamics between two consecutive samples.•Then, the sample interval is transferred into a SIA weight.•The SIA weight is multiplied to the corresponding hidden state to serve into LSTM unit.