The monitoring of production processes on a planar surface typically involves sampling network to gather information about the status of the process. In order to save time and money, when the process goes into a stable status it might be appropriate to reduce the dimension of the sampling grid. In some cases, the allocation of a new network of smaller dimension is not free of constraints and it might be necessary the selection of a subgrid extracted from the original network. Discussion is focused on some recent methods used to achieve this aim. Possible extensions to consider jointly tabu search algorithm and co-kriging models is reported.
Borgoni, R., Gilardi, A., Zappa, D., Optimal Subgrids from Spatial Monitoring Networks, in Book of short papers - IES 2022, (Capua - Caserta, 27-28 January 2022), PKE - Professional Knowledge Empowerment s.r.l., Sesto San Giovanni (MI) 2022: 148-152 [http://hdl.handle.net/10807/195824]
Optimal Subgrids from Spatial Monitoring Networks
Zappa, Diego
Ultimo
2022
Abstract
The monitoring of production processes on a planar surface typically involves sampling network to gather information about the status of the process. In order to save time and money, when the process goes into a stable status it might be appropriate to reduce the dimension of the sampling grid. In some cases, the allocation of a new network of smaller dimension is not free of constraints and it might be necessary the selection of a subgrid extracted from the original network. Discussion is focused on some recent methods used to achieve this aim. Possible extensions to consider jointly tabu search algorithm and co-kriging models is reported.
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