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Pliestić, Stjepan; Kovačev, Igor; Čopec, Krešimir; Brandić, Ivan; Galić, Ante
Krmiva, 10/2023, Volume: 65, Issue: 2Journal Article
Umjetna inteligencija (AI) i strojno učenje (ML ) sve su prisutniji u poljoprivrednom sektoru pa tako i u proizvodnji krmnih smjesa, gdje omogućuju proizvođačima optimizaciju procesa proizvodnje, smanjenje troškova i poboljšanje učinkovitosti. Implementacija nelinearnih modela, poput umjetnih neuronskih mreža (UNM ), u ovoj domeni omogućava prepoznavanje uzoraka i rješavanje kompleksnih problema povezanih s krmnim smjesama. Primjena UNM u tehnologiji proizvodnje krmnih smjesa, uz ispravno odabranu strukturu, algoritme učenja i prijenosne funkcije, omogućava naprednu optimizaciju procesa, uključujući upravljanje proizvodnim postrojenjem, skladištenje i transport sirovina. Ovi modeli pružaju nove mogućnosti za poboljšanje kvalitete krajnjeg proizvoda, uzimajući u obzir sve faktore koji na nju utječu. Kroz ovu prilagodbu, AI pruža alate za brzo i učinkovito donošenje odluka, što rezultira poboljšanom automatizacijom i učinkovitosti u proizvodnji krmnih smjesa. 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.
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