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Patients’ Preferences of Healthcare Facilities for Quality Healthcare Services in Akwa Ibom State: A Game Theory Approach

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American Journal of Operations Research 2021年第3期11卷 181-198页

作者： Vincenth Udok Udeme ukamaka cynthia orumie University of Port Harcourt Port Harcourt Nigeria

The purpose of this work is to apply Game theory approach to determine patients’ preferences of healthcare facilities for quality healthcare in Akwa Ibom State. Cross-sectional descriptive study and purposive sampling technique were adopted in order to collect the relevant data. Factors influencing patients’ preferences of health care facilities between public and private hospitals in Akwa Ibom State were assessed using a set of questionnaires which were distributed to 9976 patients in University of Uyo Teaching Hospital, Uyo, Akwa Ibom State. A two-person zero sum game theory approach was applied. Perception of quality healthcare services received by respondent’s preferred facilities between public and private hospitals was examined. Also the reasons for patients’ persistence of their preferred facilities were evaluated using questionnaire. The optimal strategy and the value of the game were determined using the factors influencing patients’ preferences of healthcare facilities, and analysed with two-person-zero-sum game. Facility that gives their clients the best satisfaction w

Modeling of Catfish Farm Using Lexicographic Linear Goal Programming

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American Journal of Operations Research 2022年第3期12卷 94-110页

作者： ukamaka cynthia orumie Egenti Francis Nzerem Chekwube Bartholomew Desmond Department of Mathematics and Statistics University of Port Harcourt Port Harcourt Nigeria Department of Statistics Federal University of Technology Owerri Owerri Nigeria

In this paper, a fish farm was modeled using the Lexicographic linear goal programming approach due to incommensurability in objectives. The study considered the fish farming plan with two sizes of catfish from stocking to harvesting at four-month intervals. The multi-objective goals developed are required raw materials feed, water, light (resource utilization), sales revenue, profit realized, labor utilization, production costs, and pond utilization. The developed model was tested using related data collected from the farm records with the use of TORA 2007 software. The compromised solution from the results showed that the developed model is an efficient tool for decision-making process in the fish farm business organization.

关键词： Goal Programming Incommensurability Lexicographic Multi-Objective Compromised Solution

Interrupted Time Series Analysis of Military and Civilian Regimes in Nigeria: A Statistical Evidence from Gross Domestic Product (GDP)

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Open Journal of Statistics 2023年第4期13卷 635-660页

作者： Desmond Chekwube Bartholomew Geoffrey Uzodinma Ugwuanyim ukamaka cynthia orumie Francis Attah Egwumah Department of Statistics Federal University of Technology Owerri Owerri Nigeria Department of Mathematics and Statistics University of Port Harcourt Port Harcourt Nigeria Department of Forestry and Wildlife Technology Federal University of Technology Owerri Owerri Nigeria

Governments influence the economy by changing the level and types of taxes, the extent and composition of spending, and the degree and form of borrowing. Governments directly and indirectly influence the way resources are used in the economy. Higher taxes, fees, and greater regulations can stymie businesses or entire industries and the resulting impact is reflected on the country’s economy status (strong or weak). The growth rate of GDP is often used as an indicator of the general health of the economy. In broad terms, an increase in real GDP is interpreted as a sign that the economy is doing well. So it is important to study and pay more attention to country’s GDP growth rate. In this paper, an intervention analysis approach was applied to Nigeria GDP data in order to evaluate the performances of military and civilian rules in the country. Data on Nigeria GDP were collected and subjected to interrupted (intervention) time series model. Based on the Alkaike Information Criterion (AIC), Bayesian Information Criterion (BIC) and sigma2 values, the interrupted time series model ARIMA (1, 1, 0) with exogenous variables (per capita per capita GDP, intervention, year and yearAfter) was identified as the best model amongst other competing models. It was observed that the intervention (civilian rule) was significant at the 10% level of significance in increasing the Nigeria GDP by 10B US$ on the average since 2005 till 2021 while controlling for the effects of other determinants. Also, the ARIMA (1, 1, 0) forecasts indicate that the Nigeria GDP will continue increasing during the civilian rule. As a result, changing from military rule to civilian rule in Nigeria significantly increased the GDP of the country.

关键词： ARIMA Forecast Gross Domestic Product Nigeria Intervention Interrupted Time Series

Modeling the Nigerian Bonny Light Crude Oil Price: The Power of Fuzzy Time Series

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Open Journal of Modelling and Simulation 2021年第4期9卷 370-3900页

作者： Desmond Chekwube Bartholomew ukamaka cynthia orumie Chukwudi Paul Obite Blessing Iheoma Duru Felix Chikereuba Akanno Department of Statistics Federal University of Technology Owerri Owerri Nigeria Department of Mathematics and Statistics University of Port Harcourt Port Harcourt Nigeria

Several authors have used different classical statistical models to fit the Nigerian Bonny Light crude oil price but the application of machine learning models and Fuzzy Time Series model on the crude oil price has been grossly understudied. Therefore, in this study, a classical statistical model—Autoregressive Integrated Moving Average (ARIMA), two machine learning models—Artificial Neural Network (ANN) and Random Forest (RF) and Fuzzy Time Series (FTS) Model were compared in modeling the Nigerian Bonny Light crude oil price data for the periods from January, 2006 to December, 2020. The monthly secondary data were collected from the Nigerian National Petroleum Corporation (NNPC) and Reuters website and divided into train (70%) and test (30%) sets. The train set was used in building the models and the models were validated using the test set. The performance measures used for the comparison include: The modified Diebold-Mariano test, the Root Mean Square Error (RMSE), the Mean Absolute Percentage Error (MAPE) and Nash-Sutcliffe Efficiency (NSE) values. Based on the performance measures, ANN (4, 1, 1) and RF performed better than ARIMA (1, 1, 0) model but FTS model using Chen’s algorithm outperformed every other model. The results recommend the use of FTS model for forecasting future values of the Nigerian Bonny Light Crude oil. However, a hybrid model of ARIMA-ANN or ARIMA-RF should be built and compared with Chen’s algorithm FTS model for the same data set to further

关键词： ARIMA Artificial Neural Network Chen’s Algorithm Fuzzy Time Series Random Forest