Progress on Artificial Neural Networks for Big Data Analytics: A Survey

IEEE Access

Nadim Rana¹  Dada Emmanuel Gbenga²  Lubna A. Gabralla³  Ala Abdulsalam Alarood⁴  Haruna Chiroma⁵  Usman Ali Abdullahi⁵  Adamu I. Abubakar⁶  Akram M. Zeki⁶  Shafi'i Muhammad Abdulhamid⁷  Liyana Shuib⁸  Tutut Herawan⁸  Ibrahim Abaker Targio Hashem⁹ 

[1] College of Computer Science and Information Systems, Jazan University, Jazan, Saudi Arabia;Department of Computer Engineering, University of Maiduguri, Nigeria;Department of Computer Science and Information Technology, Community College, Princess Nourah Bint Abdulrahman University, Riyadh, Saudi Arabia;Department of Computer Science, Faculty of Computing and Information Technology, University of Jeddah, Raids, Saudi Arabia;Department of Computer Science, Federal College of Education (Technical), Gombe, Nigeria;Department of Computer Science, International Islamic University of Malaya, Kuala Lumpur, Malaysia;Department of Cyber Security Science, Federal University of Technology, Minna, Nigeria;Department of Information Systems, Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur, Malaysia;School of Computing and IT, Taylors University, Subang Jaya, Malaysia;

关键词: Big data analytics;    artificial neural networks;    evolutionary neural network;    convolutional neural network;    dataset;   

DOI  :  10.1109/ACCESS.2018.2880694

来源: DOAJ

【 摘 要 】

Approximately 2.5 quintillion bytes of data are emitted on a daily basis, and this has brought the world into the era of “big data.” Artificial neural networks (ANNs) are known for their effectiveness and efficiency for small datasets, and this era of big data has posed a challenge to the big data analytics using ANN. Recently, much research effort has been devoted to the application of the ANN in big data analytics and is still ongoing, although it is in it is early stages. The purpose of this paper is to summarize recent progress, challenges, and opportunities for future research. This paper presents a concise view of the state of the art, challenges, and future research opportunities regarding the applications of the ANN in big data analytics and reveals that progress has been made in this area. Our review points out the limitations of the previous approaches, the challenges in the ANN approaches in terms of their applications in big data analytics, and several ANN architecture that have not yet been explored in big data analytics and opportunities for future research. We believe that this paper can serve as a yardstick for future progress on the applications of the ANN in big data analytics as well as a starting point for new researchers with an interest in the exploration of the ANN in big data analytics.

【 授权许可】

Unknown