...
首页> 外文期刊>Microprocessors and microsystems >Algorithm optimization of large-scale supply chain design based on FPGA and neural network
【24h】

Algorithm optimization of large-scale supply chain design based on FPGA and neural network

机译:基于FPGA和神经网络的大型供应链设计算法优化

获取原文
获取原文并翻译 | 示例
           

摘要

The Supply Chain Management System permits an organization to work quickly and adequately all through a large scale. It will begin with every idea?s fundamental comprehension, including Production, Inventory, Location, and Transportation. Consolidating all the cycles will underline the part of SCM (Supply chain Management) in business economics. In the existing method IoT and Convolutional Neural Network for Supply Chain Management (SCM). The drawback of the previous method is un-sensitive in the supply chain in extensive scale management. The proposed method is based on FPGA (Field Programmable Gate Arrays) and Neural Network for Supply chain Management. The outcome and looking at the finished flexibly chain the executive?s plan, and the administrator can operate without much of a stretch limit the mix-up and fix it in a brief period. Each organization has its own personal SCM (Supply Chain Management) plan, and the progression of the network domain will choose the system?s viability. The proposed Neural Network-based Numeric Framework Algorithm longchain centers on the SCM (Supply chain Management) framework?s all-out methodology and wants to have a superior SCM (Supply Chain Management). Base on the meeting date, the current Neural Network understands the positive and negative perspectives.At last, it can address the inquiries of how to improve the network framework. The organization has a more powerful SCM (Supply chain Management. Furthermore, the significant organization improves to have the option to rival the unfamiliar creations.
机译:供应链管理系统允许组织通过大规模快速和充分地工作。它将从每个想法开始,包括生产,库存,位置和运输。整合所有周期将强调商业经济学中的SCM(供应链管理)的一部分。在现有的供应链管理(SCM)的方法和卷积神经网络中。先前方法的缺点在广泛的规模管理中的供应链中是不敏感的。该方法基于FPGA(现场可编程门阵列)和用于供应链管理的神经网络。结果和观察完成的灵活连锁高管计划的计划,管理员可以在没有大部分延伸限制的情况下运行,并在短暂的时期内修复它。每个组织都有自己的个人SCM(供应链管理)计划,网络领域的进展将选择系统的可行性。基于神经网络的基于神经网络的数字框架算法Longchain中心,SCM(供应链管理)框架?S全外方法,并希望具有卓越的SCM(供应链管理)。基于会议日期,目前的神经网络了解积极和负面的观点。最后,它可以解决如何改进网络框架的询问。该组织具有更强大的SCM(供应链管理。此外,重要组织改善了可选择竞争陌生的创作。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号