Publication:

BGA solder strain prediction using an Artificial Neural Network regressor

Date

2022
Proceedings Paper
https://doi.org/10.1109/EuroSimE54907.2022.9758918
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dc.contributor.authorFerrando Villalba, Pablo
dc.contributor.authorVandevelde, Bart
dc.contributor.imecauthorFerrando Villalba, Pablo
dc.contributor.imecauthorVandevelde, Bart
dc.contributor.orcidimecVandevelde, Bart::0000-0002-6753-6438
dc.date.accessioned2023-08-21T09:46:36Z
dc.date.available2023-06-20T10:33:55Z
dc.date.available2023-08-21T09:46:36Z
dc.date.embargo9999-12-31
dc.date.issued2022
dc.description.wosFundingTextThis work has been supported by Vlaio through the INPROVOL project.
dc.identifier.doi10.1109/EuroSimE54907.2022.9758918
dc.identifier.eisbn978-1-6654-5836-8
dc.identifier.issnna
dc.identifier.urihttps://imec-publications.be/handle/20.500.12860/41829
dc.publisherIEEE
dc.source.conference23rd International Conference on Thermal, Mechanical and Multi-Physics Simulation and Experiments in Microelectronics and Microsystems (EuroSimE)
dc.source.conferencedateAPR 25-27, 2022
dc.source.conferencelocationSt Julian
dc.source.journalna
dc.source.numberofpages6
dc.title

BGA solder strain prediction using an Artificial Neural Network regressor

dc.typeProceedings paper
dspace.entity.typePublication
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