River publishers series in mathematical statistical and computational modelling for engineering data driven mathematical modeling in agriculture
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The research in this book looks at the likelihood and level of use of implemented technological components with regard to the adoption of different precision agricultural technologies. To identify the variables affecting farmers' choices to embrace more precise technology, zero-inflated Poisson and negative binomial count data regression models are utilized. Outcomes from the count data analysis of a random sample of various farm operators show that various aspects, including farm dimension, farmer demographics, soil texture, urban impacts, farmer position of liabilities, and position of the farm in a state, were significantly associated with the approval severity and likelihood of precision farming technologies.
Technical topics discussed in the book include:
Precision agriculture Machine learning Wireless sensor networks IoT Deep learning- Bekijk alle specificaties
Taal: en
Bindwijze: E-book
Oorspronkelijke releasedatum: 23 augustus 2024
Ebook Formaat: Adobe ePub
Hoofdredacteur: Sabyasachi Pramanik
Tweede Redacteur: Sandip Roy
Hoofduitgeverij: River Publishers
Lees dit ebook op: Desktop (Mac en Windows)
Lees dit ebook op: Kobo e-reader
Lees dit ebook op: Android (smartphone en tablet)
Lees dit ebook op: iOS (smartphone en tablet)
Lees dit ebook op: Windows (smartphone en tablet)
Editie: 1
Studieboek: Nee
EAN: 9781040121016