Τεχνητά νευρωνικά δίκτυα και μηχανική μάθηση σε logistics
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Keywords
Time series ; Artificial neural networks ; Logistics ; Gradient boosting ; Exponential smoothing ; ARIMAAbstract
The thesis studies the application of Artificial Neural Networks and
Machine Learning in the field of Logistics. The goal is to optimize parcel delivery by
predicting future job volume or future profit. The above forecast, businesswise can help in
better scheduling or by consolidating shipments. Grouping on shipment of products reduces
both the individual shipping cost and the human resources required to collect and ship
multiple orders. Optimizing such a process provides great business value for companies
operating in the field of logistics - forwarding. So we will study the structure and operation of
algorithms and apply some of them to a real data set, in order to attempt to predict overtime
the volumes like profit and shipment weight.
Postgraduate Studies Programme
Ψηφιακά Συστήματα και ΥπηρεσίεςDepartment
Σχολή Τεχνολογιών Πληροφορικής και Επικοινωνιών. Τμήμα Ψηφιακών ΣυστημάτωνNumber of pages
106Language
GreekCollections
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Αναφορά Δημιουργού 4.0 Διεθνές
Αναφορά Δημιουργού 4.0 Διεθνές