Épületgépészeti termékek kereslettervezése
Esettanulmány transzformer alapú neurális hálózatokkal
DOI:
https://doi.org/10.14267/VEZTUD.2024.07-08.08Kulcsszavak:
idősor előrejelzés, kereslettervezés, neurális hálózatokAbsztrakt
A hatékony kereslettervezés kritikus jelentőségű a vállalkozások számára. Ebben a kutatásban a Temporal Fusion Transformer neurális hálózat alapú modell alkalmazhatóságát vizsgálják a szerzők a kereslettervezési kihívások kezelésére. Konkrétan megvizsgálják a termékjellemzőkkel és értékesítési csatornatípusokkal kapcsolatos további információk beépítésének lehetséges előnyeit. Kutatásuk elsődleges célja e kiegészítő változók beépítésével nyert előnyök felmérése. Az elemzésben felhasznált adatállomány egy túlnyomórészt épületgépészeti termékek értékesítésével foglalkozó cégtől származik. Kezdetben a statikus tulajdonságokra, például a termékcsoportokra, majd az időben változó tulajdonságokra, például az értékesítési csatornaváltozásokra összpontosítanak. A tanulmány fő hozzájárulása az átfogó esettanulmány, amely alkalmazza a Temporal Fusion Transformer modellt a vállalat kereslettervezési problémájára, az összes specifikációjával és testreszabásával együtt.
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