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- Application of Spatial Temporal Graph Neural Network in Analyzing the Distribution of Goods Shipping...
Application of Spatial Temporal Graph Neural Network in Analyzing the Distribution of Goods Shipping with Dominating Set Technique
Authors : Ika Hesti Agustin, Binti Arianti, Dafik Dafık, Mohamad Fatekurohman, Rifki Ilham Baihaki
Pages : 10-22
Doi:10.31202/ecjse.1289020
View : 82 | Download : 182
Publication Date : 2024-03-13
Article Type : Research
Abstract :A logistics service company may face capacity issues due to distribution delays, resulting in goods accumulating in branch offices with unknown locations. To resolve this problem, we will implement the Spatial-Temporal Graph Neural Network (STGNN) combined with the dominating set technique to predict these branch office locations. The STGNN utilizes graph theory to represent relationships between branch offices in Indonesia. Simulation data on goods shipments across Indonesia are observed for 30 days, categorized as spatial-temporal data, and fed into the STGNN. This process involves three stages: node embeddings, training, and testing/forecasting. We implement some Artificial Neural Network (ANN) models with various hidden layer architectures. The results show that the best model of ANN is cascade forward metwork and the MSE 1,6714×〖10〗^(-9).Keywords : Spatial-Temporal Graph Neural Network, Goods Shipping, Logistics Services, Dominating Set