A transfer Learning-Based LSTM strategy for imputing Large-Scale consecutive missing data and its application in a water quality prediction system

•Our research object focuses on large-scale consecutive missing data.•A hybrid transfer learning-based deep learning method is proposed and illustrated.•The feasibility of the proposed algorithm in actual water monitoring is explored.•Negative Transfer is controlled within limits by a novel and classical algorithm.