Application of Artificial Neural Network in Agriculture

With the need for farming to become more efficient and environmentally sustainable to meet the demands of a growing global population, the application of artificial neural networks (ANNs) to inform and enhance agricultural practice and production is gathering momentum and interest. This Reprint titl...

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Định dạng:	Online
Ngôn ngữ:	Tiếng Anh
Được phát hành:	MDPI - Multidisciplinary Digital Publishing Institute 2025
Những chủ đề:	animal nutrition egg laying feed costs mathematical model multivariate analysis poultry pest detection GoogLeNet Convolutional Neural Network mobile application convolutional neural network Fusarium wilt transfer learning ResNet-50 banana crop solar dryer thermal analysis electronic instrumentation artificial neural networks feedforward propagation algorithm artificial neural network particle-swarm optimization specific draft specific torque equivalent PTO power rice leaf diseases blast leaf leaf folder brown spot YOLOv8 plant disease tomato machine learning deep learning bean phenology food security San Andreas fertilization model greenhouses Rhodena lettuce diseased macronutrient point clouds rice blast Magnaporthe oryzae weather parameters INGARCHX SVRX ANNX soil analysis reflectance spectra YOLO models image analysis precision agriculture pest identification tiny object recognition multi-stage detection approach edge-based processing feature integration thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
Truy cập trực tuyến:	ONIX_20250812T095121_9783725831227_43
Các nhãn:	Thêm thẻ Không có thẻ, Là người đầu tiên thẻ bản ghi này!

Miêu tả
Tóm tắt:	With the need for farming to become more efficient and environmentally sustainable to meet the demands of a growing global population, the application of artificial neural networks (ANNs) to inform and enhance agricultural practice and production is gathering momentum and interest. This Reprint titled "Application of Artificial Neural Network in Agriculture" showcases fourteen high-quality research articles highlighting the use of ANNs and related technologies for pest detection, plant disease detection, nutritional monitoring and prediction, the classification of the phenology of beans, and the optimisation of egg production. We also present how ANNs may be used for predicting the power requirements of agricultural machinery and for dynamic behaviour forecasting of an indirect solar dryer. The multidisciplinary nature of the articles presented will likely strongly appeal to researchers and scientists working in the areas of agricultural technology, communications engineering, computer science, data analytics, electronic engineering, information technology, image processing, and mathematical modelling.

Application of Artificial Neural Network in Agriculture

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