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arXiv 2102.02637cs.LGcs.AI
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大数据分析应用多准则决策与深度学习算法的融合方法

Big Data Analytics Applying the Fusion Approach of Multicriteria Decision Making with Deep Learning Algorithms

Prasad V Potluri Siddhartha Institute of Technology(普拉萨德·V·波特卢里·西达塔技术学院);Infosys Limited(印孚瑟斯有限公司);Anurag University(阿努拉格大学)

Swarajya Lakshmi V Papineni, Snigdha Yarlagadda, Harita Akkineni, A. Mallikarjuna Reddy

摘要:

数据随着人口和通信的快速发展而发展,用于各种类型的设备,诸如网络、云计算、物联网(IoT)、致动器和传感器。数据和通信内容的增加伴随着速度,速度,大小和价值的等价,以提供有用和有意义的知识,帮助解决未来具有挑战性的任务和最新的问题。此外,基于多准则的决策是解决大数据分析中与替代效应相关的各种问题的关键问题之一。它倾向于基于最新的机器学习技术找到一种解决方案,其中包括基于多标准的决策和深度学习机制等算法,以提供对大数据的见解。另一方面,对它进行了推导,使其与近似值相一致,增加了运行时的二重性,提高了整个系统的潜力和效率。从本质上讲,包括商业、农业、信息技术和计算机科学在内的多个领域都在使用深度学习和基于多标准的决策问题。本文旨在提供各种应用程序,涉及深度学习技术的概念,并利用多准则方法,在大数据分析中面临的问题,提出新的研究与数据驱动技术的融合方法。

英文摘要:

Data is evolving with the rapid progress of population and communication for various types of devices such as networks, cloud computing, Internet of Things (IoT), actuators, and sensors. The increment of data and communication content goes with the equivalence of velocity, speed, size, and value to provide the useful and meaningful knowledge that helps to solve the future challenging tasks and latest issues. Besides, multicriteria based decision making is one of the key issues to solve for various issues related to the alternative effects in big data analysis. It tends to find a solution based on the latest machine learning techniques that include algorithms like decision making and deep learning mechanism based on multicriteria in providing insights to big data. On the other hand, the derivations are made for it to go with the approximations to increase the duality of runtime and improve the entire system's potentiality and efficacy. In essence, several fields, including business, agriculture, information technology, and computer science, use deep learning and multicriteria-based decision-making problems. This paper aims to provide various applications that involve the concepts of deep learning techniques and exploiting the multicriteria approaches for issues that are facing in big data analytics by proposing new studies with the fusion approaches of data-driven techniques.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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