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1. |
Record Nr. |
UNICAMPANIASUN0019686 |
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Autore |
Meltzer, Bernard N. |
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Titolo |
L'interazionismo simbolico : genesi, sviluppi e valutazione critica / Bernard N. Meltzer, John W. Petras, Larry T. Reynolds ; edizione italiana a cura di Mario Melone |
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Pubbl/distr/stampa |
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Milano : Franco Angeli, [1980] |
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ISBN |
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Descrizione fisica |
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Altri autori (Persone) |
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Reynolds, Larry T. |
Petras, John W. |
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Disciplina |
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Soggetti |
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Interazione simbolica - Teorie |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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2. |
Record Nr. |
UNICAMPANIASUN0021053 |
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Titolo |
Air monitoring by spectroscopic techniques / edited by Markus W. Sigrist |
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Pubbl/distr/stampa |
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ISBN |
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Descrizione fisica |
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xxv, 531 p. : ill., maps ; 24 cm. |
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Disciplina |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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3. |
Record Nr. |
UNINA9910557509803321 |
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Autore |
Kujawa Sebastian |
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Titolo |
Artificial Neural Networks in Agriculture |
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Pubbl/distr/stampa |
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Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
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Descrizione fisica |
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1 online resource (283 p.) |
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Soggetti |
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Biology, life sciences |
Research & information: general |
Technology, engineering, agriculture |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Sommario/riassunto |
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Modern agriculture needs to have high production efficiency combined with a high quality of obtained products. This applies to both crop and livestock production. To meet these requirements, advanced methods of data analysis are more and more frequently used, including those |
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derived from artificial intelligence methods. Artificial neural networks (ANNs) are one of the most popular tools of this kind. They are widely used in solving various classification and prediction tasks, for some time also in the broadly defined field of agriculture. They can form part of precision farming and decision support systems. Artificial neural networks can replace the classical methods of modelling many issues, and are one of the main alternatives to classical mathematical models. The spectrum of applications of artificial neural networks is very wide. For a long time now, researchers from all over the world have been using these tools to support agricultural production, making it more efficient and providing the highest-quality products possible. |
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