Σύστημα πρόβλεψης τρύγου μελιού βασισμένο σε Spring Boot Framework

Τζεμπελίκου, Σοφία

Honey harvesting predictor with Spring Boot Framework

Master Thesis

Author

Τζεμπελίκου, Σοφία

Date

2022-07

Abstract

As the need for the development of science and technology grows daily, so does the need to develop models that mimic human reason and human judgment. One area that much research focuses on is the use of machine learning to draw conclusions similar to human logic. This dissertation analyzes the use of machine learning in agriculture and more specifically in beekeeping in order to predict the harvest season of bees and then makes a statistical analysis in order to compare production between time periods and the impact of weather conditions on production. of honey.

Postgraduate Studies Programme

Προηγμένα Συστήματα Πληροφορικής - Ανάπτυξη Λογισμικού και Τεχνητής Νοημοσύνης

Department

Σχολή Τεχνολογιών Πληροφορικής και Επικοινωνιών. Τμήμα Πληροφορικής

Number of pages

Language

Greek

URI

https://dione.lib.unipi.gr/xmlui/handle/unipi/14496
http://dx.doi.org/10.26267/unipi_dione/1919

Collections

Τμήμα Πληροφορικής

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Except where otherwise noted, this item's license is described as
Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ελλάδα