Titlebook: Robotics, Machinery and Engineering Technology for Precision Agriculture; Proceedings of XIV I Mark Shamtsyan,Marco Pasetti,Alexey Beskopyl

gloomy

书目名称Robotics, Machinery and Engineering Technology for Precision Agriculture影响因子(影响力)




书目名称Robotics, Machinery and Engineering Technology for Precision Agriculture影响因子(影响力)学科排名




书目名称Robotics, Machinery and Engineering Technology for Precision Agriculture网络公开度




书目名称Robotics, Machinery and Engineering Technology for Precision Agriculture网络公开度学科排名




书目名称Robotics, Machinery and Engineering Technology for Precision Agriculture被引频次




书目名称Robotics, Machinery and Engineering Technology for Precision Agriculture被引频次学科排名




书目名称Robotics, Machinery and Engineering Technology for Precision Agriculture年度引用




书目名称Robotics, Machinery and Engineering Technology for Precision Agriculture年度引用学科排名




书目名称Robotics, Machinery and Engineering Technology for Precision Agriculture读者反馈




书目名称Robotics, Machinery and Engineering Technology for Precision Agriculture读者反馈学科排名

组成

神化怪物

Quality Control of Frame Structures of Robotic Systems by Express Nondestructive Methods,he fundamental principles of ensuring the quality of parts using express nondestructive methods of impact indentation of conical indenters using artificial intelligence algorithms. The quality of parts is considered from the standpoint of a set of mechanical properties that determine strength, hardn

Diastole

发酵

CRUC

窃喜

Use of Neural Networks and Autopilot for Quick and Accurate Grain Discharge on the Elevator,tten in C# and allows solving two problems: automatic detection of a free port for unloading grain and the use of an autopilot to supply a vehicle to a loading or unloading terminal. To determine the boundaries of the parking space or to determine a free port for unloading grain, image recognition u

abject

Operation of Membrane Apparatus with Polarization Layer Removal Using Artificial Neural Networks,rks. The neural network was trained using the results of experiments, where the technological parameters of the apparatus were changed, and the dry matter concentration rate per meter of the filter area was measured. The resulting neural network showed high accuracy, topping the other modeling metho

CANON

brother