Jul 24, 2021 · This paper uses the GM (1,1) model to directly predict input indicators, and then fit the relationship between input and output indicators ...
This paper uses the GM (1,1) model to directly predict input indicators, and then fit the relationship between input and output indicators through BP neural ...
And the classification model based on BP neural network is established and evaluated through experiments, which are proved that a classification data mining ...
The empirical results show that the IPSO-GNN model has high precision and strong stability, which can predict port logistics demand effectively. ResearchGate ...
In this paper, GM-BP neural network combines grey system theory and neural network technology, which can improve the stability and robustness of the prediction ...
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The empirical results show that the IPSO-GNN model has high precision and strong stability, which can predict port logistics demand effectively.
Missing: Efficiency | Show results with:Efficiency
A Study of Logistics Efficiency Prediction in Dalian Port Based on Gray-BP Neural NetworkTong Lu, Zhongliang Guan. 169-174 [doi] · Analysis of District ...
A Study of Logistics Efficiency Prediction in Dalian Port Based on Gray-BP Neural Network. ICMSS 2021: 169-174; 2020. [c9]. view. electronic edition via DOI ...
In this paper, the output of cold chain agricultural products is used as the predictor index to establish an index system of influencing factors of cold chain ...
Missing: Efficiency | Show results with:Efficiency
Hu, Prediction algorithm of port cargo throughput based on grey neural network ... Research on Port Logistics Demand Forecast Based on GRA-WOA-BP Neural Network.
Missing: Gray- | Show results with:Gray-