Results 241 to 250 of about 3,356 (285)

An efficient assignment of multiple agricultural machinery tasks based on Chaotic Cauchy Elite Variable Snake Optimization Algorithm. [PDF]

PLoS One
Xiang R, Liu X, Tian M, Ban C, Li R, Zhou J.   +5 more
europepmc   +1 more source

Modeling and experimental validation of bolt–grout bond–slip behavior for deep underground excavation support

Deep Underground Science and Engineering, EarlyView.
A novel shear‐lag model, validated by pull‐out tests, incorporates a constant bond stress stage to predict the complete load–displacement response of grouted rock bolts, providing a new tool for optimizing anchorage length and material toughness in deep underground engineering. Abstract The stability of rock masses in deep underground excavations, such
Wenhui Bian, Xiaohui He, Kexue Wang, Yufei Wu, Guoxin Wang, Shaochen Zhang, Jun Yang   +6 more
wiley   +1 more source

LMRNet: a lightweight convolutional neural network for real-time mountain rice leaf disease recognition on edge devices. [PDF]

Front Plant Sci
Cui J, Yang Y, Chen Z, Hao S, Tan F.
europepmc   +1 more source

Study on the impact of new quality productive forces on agricultural green production efficiency. [PDF]

Sci Rep
Lei X, Zhao W, Du H.
europepmc   +1 more source

Identifying systemic risks and mitigation strategies of artificial intelligence in agriculture: from social-technical-ecological systems framework. [PDF]

Front Plant Sci
Yuan Y, Sun Y.
europepmc   +1 more source

Path tracking control method for tracked agricultural vehicles based on slip-aware look-ahead point offset. [PDF]

Front Plant Sci
Liu H, Han Z, Yin J, Bao J, Mu J, Tan H, Liu X.   +6 more
europepmc   +1 more source

Adaptive path tracking control of unmanned agricultural machinery with fixed-time super-twisting sliding mode based on RLS-ELM. [PDF]

Front Plant Sci
Chen Z, Yin J, Farhan SM, Lin Z, Zhou M.
europepmc   +1 more source

YOLO-LSBA: A high-precision model for detecting stems of small-sized cherry tomatoes. [PDF]

Sci Rep
Liu Q, Chen F, Zhang H, Cao B, Yang J, Zhang N, Qiao Y, Liu Z, Mao J, Chen M.   +9 more
europepmc   +1 more source

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Development of an Intelligent Monitoring System for Agricultural Machinery

2019 3rd International Conference on Robotics and Automation Sciences (ICRAS), 2019
In order to monitor the working states and working environment of agricultural machinery in real time, an intelligent monitoring system based on I.MX6 is developed in this paper. Through USB, CAN and RS485, the environment videos, positions and working states of agricultural machinery are collected.
Yu Fei, Ying Zhuang, Xiang Liu, Qichun Zhao, Gonglei Liao, Qiang Fu   +5 more
exaly   +2 more sources