首页|Recent Studies from Faculty of Agrobiotechnical Sciences Osijek Add New Data to Machine Learning (Machine Learning Methods for Evaluation of Technical Factors o f Spraying in Permanent Plantations)
Recent Studies from Faculty of Agrobiotechnical Sciences Osijek Add New Data to Machine Learning (Machine Learning Methods for Evaluation of Technical Factors o f Spraying in Permanent Plantations)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on ar tificial intelligence. According to news reporting originating from Osijek, Croa tia, by NewsRx correspondents, research stated, “Considering the demand for the optimization of the technical factors of spraying for a greater area coverage an d minimal drift, field tests were carried out to determine the interaction betwe en the area coverage, number of droplets per cm2, droplet diameter, and drift.” Our news editors obtained a quote from the research from Faculty of Agrobiotechn ical Sciences Osijek: “The studies were conducted with two different types of sp rayers (axial and radial fan) in an apple orchard and a vineyard. The technical factors of the spraying interactions were nozzle type (ISO code 015, code 02, an d code 03), working speed (6 and 8 km h-1), and spraying norm (250-400 L h-1). T he airflow of both sprayers was adjusted to the plantation leaf mass and the wor king pressure was set for each repetition separately. A method using water-sensi tive paper and a digital image analysis was used to collect data on coverage fac tors. The data from the field research were processed using four machine learnin g models: quantile random forest (QRF), support vector regression with radial ba sis function kernel (SVR), Bayesian Regularization for Feed-Forward Neural Netwo rks (BRNN), and Ensemble Machine Learning (ENS). Nozzle type had the highest pre dictive value for the properties of number of droplets per cm2 (axial = 69.1% ;radial = 66.0%), droplet diameter (axial = 30.6%; ra dial = 38.2%), and area coverage (axial = 24.6%; radia l = 34.8%).”
Faculty of Agrobiotechnical Sciences Osi jekOsijekCroatiaEuropeCyborgsEmerging TechnologiesMachine Learning
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