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Author(s): Akpome Jennifer Nomuoja, Chidera Agu, Temisan Gabriel Olawale , Chinyere Josephine, Emwinloghosa Kenneth Guobadia.

Volume/Issue: Volume 7 , Issue 4 (2024)

Abstract:

In this paper, the record is set straight on the technique for the development of classical distributions; where a new model called the Sky-Log distribution is proposed as an illustrative example of the methodical approach. The statistical properties of the proposed distribution were derived; and the very many known generating functions there is, exist for the distribution. Lionel Messi’s football record data were analyzed to validate the essence of the proposed model. Finally, it was discovered that the proposed distribution sub-model, termed Sky-X distribution, and the exponential distribution, are exact model fit alternatives.

Keywords:

Model Theory, Probability distribution, Sky-Log distribution, Sky-X distribution, Lifetime data, Generating function.

No. of Downloads: 0

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Author(s): Owoyi M. C., Okwonu F. Z..

Volume/Issue: Volume 7 , Issue 4 (2024)

Abstract:

Imbalanced data are often delegate issues in data set as it has the power to affect the result and the performance of the classification algorithm. In such problems, if not handled well with a good sampling techques could lead to biased result, overfitting as well as high rate of misclassification thereby favouring just one class among the two classes. Usually, when assigning a sampling techniques, it is necessary to look at the nature of the dataset being studied. It is of a truth that the LDA classifier looking for an efficient performance when presented with an imbalanced instances are not suitable to deal with imbalanced learning tasks, since they tend to classify all the data into the majority class, which is usually the less important class. This work explains the different approaches which have been employed by different researchers to resolve the issue of imbalanced data in LDA and the effect of the result obtained both positively and negatively. It should be noted that this single article cannot completely review all the works or researches done on the topic, hence we hope that the references which was dually cited will be of help to the major theoretical issues.

Keywords:

Imbalanced data; Oversampling; Undersampling; Classification; Metric evaluation.

No. of Downloads: 0

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Author(s): Raphael Michael Ugochukwu, Odo Kenneth Ejiofor, Nwanya J. C..

Volume/Issue: Volume 7 , Issue 4 (2024)

Abstract:

This study looks at the optimality criteria performances on the factorial design of Resolution IV and Resolution V. The Comparative studies of Resolution IV and Resolution V design were evaluated using the D, G, and I-optimality criteria. The FDS plots where also used. The results showed that in all the factors k considered, Resolution V has a better factorial design when it comes to D- optimality, G- optimality and I-optimality, but when the interest is on the spread of the scale prediction variance, Resolution IV is preferred. The FDS plots for Resolution IV and V design were relatively the same for factors k = 6 and k = 10.

Keywords:

Optimality criteria, resolution iv and resolution v, factorial designs, D-optimality, I-optimality, G-optimality, Design matrix, Fraction of Design Space (FDS) Plots.

No. of Downloads: 0

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Author(s): Robert Folorunsho Akerejola (Ph.D.), Elakhe O. A., Isere A. O..

Volume/Issue: Volume 7 , Issue 4 (2024)

Abstract:

In this research work, a dynamically consistent non-standard finite difference (NSFD) scheme is developed to solve a continuous-time model of malaria transmission with herbal medicine as control strategy. We compared results from NSFD scheme with the standard finite difference methods (4th order Runge-kutta and forward Euler methods). The numerical investigation showed that the proposed NSFD method remains consistent, preserves the positivity of solutions and converges to true equilibrium points of the continuous model independent of the step size h.

Keywords:

Non-Standard Finite Difference, Herbal, Malaria, Runge-kutta, Uncomplicated.

No. of Downloads: 0

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Author(s): Samuel Hwere Tsok, Sabo Hama, M. S. Adamu.

Volume/Issue: Volume 7 , Issue 4 (2024)

Abstract:

This paper delves into exploration of primitivity and regularity of Dihedral groups of degree 5p, where p is prime, focusing on cases where these groups are not p-groups. By utilizing numerical approaches, the properties of these groups are examined to shed light on their structure, behavior, and underlying algebraic characteristics. Key numerical methods are employed to calculate invariants and test conditions for primitivity and regularity in these groups. [20][13]

Keywords:

Dihedral groups, Primitivity, Regularity, Numerical approach, GAP.

No. of Downloads: 0

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Author(s): Agbedeyi O. D., Maliki S. O., Asor V. E..

Volume/Issue: Volume 7 , Issue 4 (2024)

Abstract:

In this research work, we developed a predictive model for digital currency prices, involving daily closing price as a function of time. We used the Geometric Brownian motion stochastic differential equation which was solved using inbuild functions in Microsoft Excel. While we used the Bitcoin as our case study, our model was able to predict the daily closing prices of Bitcoin to a reasonable degree of accuracy. We equally observe that the time dependent Geometric Brownian motion stochastic differential equation cannot give digital currency traders and investors a clue on when to trade off their digital assets. Thus, it become very risky using our model to make well informed trading decisions. We therefore, recommend that for minimum risk, trades and investors in digital currencies should consider a combination of other signal tools to take more informed and less risky trading decisions.

Keywords:

Crypto Currency, Geometric Brownian motion, Bitcoin, Stochastic Modelling.

No. of Downloads: 0

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Author(s): Agbedeyi O. D., Maliki S. O., Asor V. E..

Volume/Issue: Volume 7 , Issue 4 (2024)

Abstract:

In this research work, we developed a mathematical model of a digital currency market, involving daily closing price as a function of time. We proposed the Artificial Neural Network (ANN) model. We observed that our ANN model was able to predict the daily closing price of Bitcoin and also make six weeks forecast to a reasonable degree of accuracy. We equally observe that the time dependent ANN model can actually give digital currency traders and investors a clue on when to trade off their digital assets with minimum risk. We therefore, recommend that ANN model should be incorporated into digital currency trading platforms as a signal tool to enable digital currency traders take more informed and less risky trading decisions. From our findings, we would advise traders who wish to employ ANN model to consider a smaller time frame say a few weeks’ time interval for their predictions. We observed also that ANN models have limitations when it comes to manual computation or implementation in Microsoft Excel, especially when dealing with very large input values. This is because of the saturation characteristic of our ANN inner layer activation function (viz; tanh function) which can lead to identical output values for different input values, making it difficult to replicate the ANN model's behavior. Furthermore, ANN models often involve complex interactions between multiple neurons, layers, and activation functions, which can be challenging to replicate manually.

Keywords:

Digital Currencies, Artificial Neural Network, Bitcoin, Stochastic Modelling.

No. of Downloads: 0

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Author(s): Mark Nwachukwu Ugo, John Paul Kenechukwu Iwuchukwu, Emwinloghosa Kenneth Guobadia.

Volume/Issue: Volume 7 , Issue 4 (2024)

Abstract:

The paper reviews creative ways to developing continuous probability models playing around integration method and the concept of normalization. It further projects a probability distribution realized by combining two symmetric probability models that differ in shape, to produce a perfect hemisphere or half-sun trend. Normal and arcsine distributions are the root distributions used for this development. At some values of the parameter, the distribution can be right skewed; where other moments and related measures, and estimation are studied as its properties, alongside simulation.

Keywords:

Normal distribution, Arcsine distribution, Division arrangement, Hemisphere trend.

No. of Downloads: 0