Deep Learning Algorithms and Multicriteria Decision-Making Used in Big Data: A Systematic Literature Review

Mei Yang, Shah Nazir, Qingshan Xu and Shaukat Ali

Complexity, 2020, vol. 2020, 1-18

Abstract:

The data are ever increasing with the increase in population, communication of different devices in networks, Internet of Things, sensors, actuators, and so on. This increase goes into different shapes such as volume, velocity, variety, veracity, and value extracting meaningful information and insights, all are challenging tasks and burning issues. Decision-making based on multicriteria is one of the most critical issues solving ways to select the most suitable decision among a number of alternatives. Deep learning algorithms and multicriteria-based decision-making have effective applications in big data. Derivations are made based on the use of deep algorithms and multicriteria. Due to its effectiveness and potentiality, it is exploited in several domains such as computer science and information technology, agriculture, and business sector. The aim of the proposed study is to present a systematic literature study in order to show the applications of deep learning algorithms and multicriteria decision approaches for the problems of big data. The research finds novel means to make the decision support system for the problems of big data using multiple criteria in integration with machine learning and artificial intelligence approaches.

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:hin:complx:2836064

DOI: 10.1155/2020/2836064

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