Review article

https://doi.org/10.33128/k.65.2.2

Application of machine learning models in the feed mixture production

Ante Galić orcid.org/0000-0002-0155-7228 ; Agronomski fakultet Sveučilišta u Zagrebu, Svetošimunska cesta 25, Zagreb, Hrvatska
Stjepan Pliestić ; Agronomski fakultet Sveučilišta u Zagrebu, Svetošimunska cesta 25, Zagreb, Hrvatska
Igor Kovačev ; Agronomski fakultet Sveučilišta u Zagrebu, Svetošimunska cesta 25, Zagreb, Hrvatska
Krešimir Čopec ; Agronomski fakultet Sveučilišta u Zagrebu, Svetošimunska cesta 25, Zagreb, Hrvatska
Ivan Brandić orcid.org/0000-0003-4135-8757 ; Agronomski fakultet Sveučilišta u Zagrebu, Svetošimunska cesta 25, Zagreb, Hrvatska

Abstract

Artificial intelligence (AI) and machine learning (ML) are increasingly present in agriculture, particularly in the production of feed mixtures, where they enable producers to optimize production processes, reduce costs, and improve efficiency. The implementation of nonlinear models, such as artificial neural networks (UNM), in this field enables pattern recognition and the solution of complex problems related to feed mixtures. The application of UNM in the technology of feed mixture production, with a properly chosen structure, learning algorithms and transfer functions, allows advanced optimization of the process, including the management of the production plant, storage and transportation of materials. These models offer new opportunities to improve the quality of the final product, taking into account all the factors that influence it. Through this customization, AI provides tools for fast and efficient decision making, leading to improved automation and efficiency in compound feed production.

Keywords

Artificial intelligence; machine learning; optimization; modelling; feed mixtures

Hrčak ID:

308549

URI

https://hrcak.srce.hr/308549

Publication date:

6.10.2023.

Article data in other languages: croatian

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