{"title":"Smart farming in agricultural industry: Mobile technology perspective","authors":"Žarko Rađenović, B. Krstić, M. Marković","doi":"10.5937/ekopolj2003925r","DOIUrl":null,"url":null,"abstract":"The aim of this research is to examine key indicators that are necessary for the implementation and development of smart farming concepts in the agricultural industry, especially from the applied mobile technology point of view. Accordingly, the authors used a neural network based software solution to determine the correlation, relationship structure and partial contribution of indicators for the mobile technology development in agricultural industries in selected countries. The validity of the input-output model in a neural network based software solution was evaluated using the Minkowski error and Quasi-Newton method through several iterations/epochs. The neural network structure has shown the importance of particular indicators for adopting a mobile technology perspective in the agricultural industry, where the application of Information and Communications Technologies (ICT) in agriculture is most emphasized. Only those countries that invest the most in the ICT in the agricultural sector can achieve greater efficiency and productivity by applying smart farming. © 2020 EA. All rights reserved.","PeriodicalId":45567,"journal":{"name":"Ekonomika Poljoprivreda-Economics of Agriculture","volume":"67 1","pages":"925-938"},"PeriodicalIF":0.8000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ekonomika Poljoprivreda-Economics of Agriculture","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5937/ekopolj2003925r","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"AGRICULTURAL ECONOMICS & POLICY","Score":null,"Total":0}
引用次数: 4
农业中的智能农业:移动技术视角
本研究的目的是研究在农业中实施和发展智能农业概念所必需的关键指标,特别是从应用移动技术的角度来看。据此,作者利用基于神经网络的软件解决方案确定了选定国家农业产业移动技术发展指标的相关性、关系结构和部分贡献。利用Minkowski误差和准牛顿方法,通过多次迭代/迭代,对基于神经网络的软件解的输入-输出模型的有效性进行了评估。神经网络结构显示了在农业中采用移动技术视角的特定指标的重要性,其中信息和通信技术(ICT)在农业中的应用是最强调的。只有那些在农业部门投资信息通信技术最多的国家才能通过应用智能农业实现更高的效率和生产力。©2020 EA保留所有权利。
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