In order to ensure the quality and safety of agricultural and sideline products,remote monitoring technol-ogy based on multi-sensor has been widely used in agricultural cold chain transportation industry.The traditional cold chain transportation environmental monitoring and prediction technology mainly combines the analysis of vari-ous environmental indicators,and does not effectively integrate and fit the heterogeneous and unbalanced data.In this paper,a K-LSTM fusion and prediction algorithm model is proposed based on the pre-trained convolution en-coder,attention mechanism and long and short memory network(LSTM).The experimental results show that the fusion accuracy of the K-LSTM algorithm reaches 96%,which is 20%～70%higher than the index results of the literatures.Therefore,the K-LSTM proposed in this paper can accurately predict the temperature and humidity in-side the refrigerated carriage,which provides effective support for the intelligent management of the cold chain.
维普
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