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All Journal Journal of Applied Science, Engineering, Technology, and Education Quantitative Economics and Management Studies
Otakore, Oghenevwede Debby
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Industrial & Manufacturing Engineering Mathematics Other

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Forging An Optimized Bayesian Network Model With Selected Parameters For Detection of The Coronavirus In Delta State of Nigeria Ojugo, Arnold; Otakore, Oghenevwede Debby
Journal of Applied Science, Engineering, Technology, and Education Vol. 3 No. 1 (2021)
Publisher : Yayasan Ahmar Cendekia Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (495.914 KB) | DOI: 10.35877/454RI.asci2163

Abstract

Machine learning algorithm have become veritable tools for effective decision support towards the construction of systems that assist experts (individuals) in their field of exploits and endeavor with regards to problematic tasks.. They are best suited for tasks where data is explored and exploited; and cases where the dataset contains noise, partial truth, ambiguities and in cases where there is shortage of datasets. For this study, we employ the Bayesian network to construct a model trained towards a target system that can help predict best parameters used for classification of the novel coronavirus (covid-19). Data was collected from Federal Medical Center Epidemiology laboratory (a centralized databank for all cases of the covid-19 in Delta State). Data was split into training and investigation (test) dataset for the target system. Results show high predictive capability.
Investigating The Unexpected Price Plummet And Volatility Rise In Energy Market: A Comparative Study of Machine Learning Approaches Ojugo, Arnold Adimabua; Otakore, Oghenevwede Debby
Quantitative Economics and Management Studies Vol. 1 No. 3 (2020)
Publisher : Yayasan Ahmar Cendekia Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (658.006 KB) | DOI: 10.35877/454RI.qems12119

Abstract

The energy market aims to manage risks associated with prices and volatility of oil asset. It is a capital-intensive market that is rippled with chaos and complex interactions among its demand-supply derivatives. Models help users forecast such interactions, to provide investors with empirical evidence of price direction. Our study sought to investigate the reasons for the unexpected plummet in price of the energy market using evolutionary modeling – which seeks to analyze input data and yield an optimal, complete solution that are tractable, robust and low-cost with tolerance of ambiguity, uncertainty and noise. We adopt the Gabillon’s model to: (a) predict spots/futures prices, (b) investigate why previous predictions failed as to why price plummet, and (c) seek to critically evaluate values reached by both proposed deep learning model and the memetic algorithm by Ojugo and Allenotor (2017).
Intelligent Peer-To-Peer Banking Framework: Advancing The Frontiers of Agent Banking For Financial Inclusion In Nigeria Via Smartphones Ojugo, Arnold Adimabua; Otakore, Oghenevwede Debby
Quantitative Economics and Management Studies Vol. 1 No. 5 (2020)
Publisher : Yayasan Ahmar Cendekia Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (800.741 KB) | DOI: 10.35877/454RI.qems140

Abstract

The advent of the retail point of sale (POS) system as a critical component of the traditional retail infrastructure seeks to advance client payment-ease for goods and services rendered by vendors as well as the effective collection of funds by the vendor. It also aids the vendor to collect in advance monies that the client may wish to spend later on goods and services. Thus, the POS has since become a necessity in modern retail stores as its increased usage has seen a transformation from a single machine to a cloud and smart platforms. Our study seeks to model a conceptual framework for decentralized POS as adapted to smartphones. This will enhance cashless transaction irrespective of a customer’s location globally and locally. Built around the block-chain technology, it seeks to minimize challenge(s) of time, installation requirements incurred with the adoption of automatic teller machine (ATM), location and citing of agent-banking in a rural area with low tele- and tech-penetration.
Co-Authors Ojugo, Arnold Ojugo, Arnold Adimabua