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农业古籍断句标点模式研究 总被引:4,自引:0,他引:4
农业古籍的整理已经引起了众多学者和专家的注意,但是,对于农业古籍的自动断句、标点模式的研究仍付之阙如。本研究探索并总结出部分农业古籍断句、标点识别模式。首先采用句法特征词断句法、同义语标志词法进行初步断句;进而利用反义复合词、引书标志、时序、数量词、重叠字词、动名结构及比较句法进一步对子句进行断句、标点;最后使用农业用语和禁用模式表进一步提高断句、标点后农业古籍的可读性和准确性。经测试表明,断句、标点的平均准确率分别达到48%和35%,证明本方法具有一定的正确性和可行性。 相似文献
13.
In recent years, the usage and applications of Internet of Things (IoT) have increased exponentially. IoT connects multiple heterogeneous devices like sensors, micro controllers, actuators, smart devices like mobiles, watches, etc. IoT contributes the data produced in the context of data collection, including the domains like military, agriculture, healthcare, etc. The diversity of possible applications at the intersection of the IoT and the web semantics has prompted many research teams to work at the interface between these two disciplines. This makes it possible to collect data and control various objects in transparent way. The challenge lies in the use of this data. Ontologies address this challenge to meet specific data needs in the IoT field. This paper presents the implementation of a dynamic agriculture ontology-building tool that parses the ontology files to extract full data and update it based on the user needs. The technology is used to create the angular library for parsing the OWL files. The proposed ontology framework would accept user-defined ontologies and provide an interface for an online updating of the owl files to ensure the interoperability in the agriculture IoT. 相似文献
14.
A country’s economy heavily depends on agricultural development. However, due to several plant diseases, crop growth rate and quality are highly suffered. Accurate identification of these diseases via a manual procedure is very challenging and time-consuming because of the deficiency of domain experts and low-contrast information. Therefore, the agricultural management system is searching for an automatic early disease detection technique. To this end, an efficient and lightweight Deep Learning (DL)-based framework (E-GreenNet) is proposed to overcome these problems and precisely classify the various diseases. In the end-to-end architecture, a MobileNetV3Small model is utilized as a backbone that generates refined, discriminative, and prominent features. Moreover, the proposed model is trained over the PlantVillage (PV), Data Repository of Leaf Images (DRLI), and a new Plant Composite (PC) dataset individually, and later on test samples, its actual performance is evaluated. After extensive experimental analysis, the proposed model obtained 1.00%, 0.96% and 0.99% accuracies on all three included datasets. Moreover, the proposed method achieves better inference speed when compared with other State-Of-The-Art (SOTA) approaches. In addition, a comparative analysis is conducted where the proposed strategy shows tremendous discriminative scores as compared to the various pre-trained models and other Machine Learning (ML) and DL methods. 相似文献
15.
Hesheng Yin Qixin Sun Xu Ren Junlong Guo Yunlong Yang Yujia Wei Bo Huang Xiujuan Chai Ming Zhong 《野外机器人技术杂志》2023,40(6):1363-1387
Citrus harvesting is a labor-intensive and time-intensive task. As the global population continues to age, labor costs are increasing dramatically. Therefore, the citrus-harvesting robot has attracted considerable attention from the business and academic communities. However, robotic harvesting in unstructured and natural citrus orchards remains a challenge. This study aims to address some challenges faced in commercializing citrus-harvesting robots. We present a fully integrated, autonomous, and innovative solution for citrus-harvesting robots to overcome the harvesting difficulties derived from the natural growth characteristics of citrus. This solution uses a fused simultaneous localization and mapping algorithm based on multiple sensors to perform high-precision localization and navigation for the robot in the field orchard. Besides, a novel visual method for estimating fruit poses is proposed to cope with the randomization of citrus growth orientations. Further, a new end-effector is designed to improve the success and conformity rate of citrus stem cutting. Finally, a fully autonomous harvesting robot system has been developed and integrated. Field evaluations showed that the robot could harvest citrus continuously with an overall success rate of 87.2% and an average picking time of 10.9 s/fruit. These efforts provide a solid foundation for the future commercialization of citrus-harvesting robots. 相似文献
16.
Ahmed Abdu Alattab Mohammed Eid Ibrahim Reyazur Rashid Irshad Anwar Ali Yahya Amin A. Al-Awady 《计算机、材料和连续体(英文)》2023,74(2):2397-2412
This research proposes a machine learning approach using fuzzy logic to build an information retrieval system for the next crop rotation. In case-based reasoning systems, case representation is critical, and thus, researchers have thoroughly investigated textual, attribute-value pair, and ontological representations. As big databases result in slow case retrieval, this research suggests a fast case retrieval strategy based on an associated representation, so that, cases are interrelated in both either similar or dissimilar cases. As soon as a new case is recorded, it is compared to prior data to find a relative match. The proposed method is worked on the number of cases and retrieval accuracy between the related case representation and conventional approaches. Hierarchical Long Short-Term Memory (HLSTM) is used to evaluate the efficiency, similarity of the models, and fuzzy rules are applied to predict the environmental condition and soil quality during a particular time of the year. Based on the results, the proposed approaches allows for rapid case retrieval with high accuracy. 相似文献
17.
FRANZEN Aaron 《中国科学:信息科学(英文版)》2011,(3)
In this research, a closed-loop drip irrigation control hybrid wireless sensor and actuator network (HWSAN) prototype were developed and deployed in a crop field for soil property precise measurement and precision irrigation in accordance with the measured soil property. The HWSAN was composed of a wireless sensor and actuator network (WSAN) used for in-field soil property monitoring and irrigation control and a laboratory supervising system. The WSAN included ten sensor nodes, five irrigation control nodes... 相似文献
18.
Jean‐Paul M. Arnaout Marwan Maatouk 《International Transactions in Operational Research》2010,17(5):595-605
The agriculture sector still lacks the tools and models to enhance the utilization of different resources. This paper addresses the vineyard harvesting problem in developing countries, with the objective of optimizing the wine quality and minimizing the operational costs. Heuristics were introduced to better assign the harvesting days to the different grape blocks that exist in the vineyard's field. The quality of the grapes was a key target as it can transform production from a pinnacle wine to a bulk one. We solved several numerical examples for verification and demonstrative purposes and found that our proposed approach finds solutions that significantly reduce the harvesting costs in the vineyard and considerably outperform Branch and Bound algorithm especially for large problems. 相似文献
19.
通过使用物联网(IOT)传输协议—消息队列遥测传输(MQTT)协议,将前端硬件、服务器端及移动端连接在一起,完成对设施农业环境的远程实时监控.在系统中,前端硬件以STM32微处理器为核心,由传感器模块、设备控制模块、GPRS模块和电源模块组成,实现数据的采集和传输;服务器端有数据接收、存储、分析的能力,并担任MQTT消息协议中消息生产者和消息管理者的角色;移动终端软件则以Android操作系统为基础开发了应用软件,用户在装有Android系统的移动终端上安装该应用软件,即可查看实时环境情况,发送控制设备指令等.经过测试,整个系统运行稳定、使用简单、实时性高,用户能有效地对设施农业环境进行远程实时监控. 相似文献
20.
基于Android技术、计算机网络技术设计了智慧农业控制系统手机APP客户端、上位机软件,搭建了服务器.上位机作为服务器和硬件控制系统中介,实时接收硬件系统的农作物环境信息,并通过服务器保存.APP客户端实时获取服务器信息,直观形象呈现给用户,且可以设置参数报警阀值,及时提醒用户,用户可选择智能模式或者手动模式远程调节农作物生长环境因素. 相似文献