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Article

A Deep Neural Network-Based Advisory Framework for Attainment of Sustainable Development Goals 1-6

1
Centre for Information and Technology, University of Lagos, Lagos 100001, Nigeria
2
Department of Informatics, Technical University of Munich, 80333 Munich, Germany
3
Department of Electrical & Information Engineering (EIE), College of Engineering, Covenant University, Ogun 112233, Nigeria
4
Department of Information Systems Engineering, Faculty of Engineering, Atilim University, 06830 Incek, Ankara, Turkey
*
Author to whom correspondence should be addressed.
Sustainability 2020, 12(24), 10524; https://doi.org/10.3390/su122410524
Received: 21 October 2020 / Revised: 10 December 2020 / Accepted: 11 December 2020 / Published: 16 December 2020
Research in sustainable development, program design and monitoring, and evaluation requires data analytics for the Sustainable Developments Goals (SDGs) not to suffer the same fate as the Millennium Development Goals (MDGs). The MDGs were poorly implemented, particularly in developing countries. In the SDGs dispensation, there is a huge amount of development-related data that needs to be harnessed using predictive analytics models such as deep neural networks for timely and unbiased information. The SDGs aim at improving the lives of citizens globally. However, the first six SDGs (SDGs 1-6) are more relevant to developing economies than developed economies. This is because low-resourced countries are still battling with extreme poverty and unacceptable levels of illiteracy occasioned by corruption and poor leadership. Inclusive innovation is a philosophy of SDGs as no one should be left behind in the global economy. The focus of this study is the implementation of SDGs 1-6 in less developed countries. Given their peculiar socio-economic challenges, we proposed a design for a low-budget deep neural network-based sustainable development goals 1-6 (DNNSDGs 1-6) system. The aim is to empower actors implementing SDGs in developing countries with data-based information for robust decision making. View Full-Text
Keywords: sustainability development goals; predictive analytics models; developing economies; deep neural network sustainability development goals; predictive analytics models; developing economies; deep neural network
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MDPI and ACS Style

Emmanuel, O.; M, A.; Misra, S.; Koyuncu, M. A Deep Neural Network-Based Advisory Framework for Attainment of Sustainable Development Goals 1-6. Sustainability 2020, 12, 10524. https://doi.org/10.3390/su122410524

AMA Style

Emmanuel O, M A, Misra S, Koyuncu M. A Deep Neural Network-Based Advisory Framework for Attainment of Sustainable Development Goals 1-6. Sustainability. 2020; 12(24):10524. https://doi.org/10.3390/su122410524

Chicago/Turabian Style

Emmanuel, Okewu, Ananya M, Sanjay Misra, and Murat Koyuncu. 2020. "A Deep Neural Network-Based Advisory Framework for Attainment of Sustainable Development Goals 1-6" Sustainability 12, no. 24: 10524. https://doi.org/10.3390/su122410524

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