Intuitionistic Fuzzy Set and Its Application in Corona Covid-19
Abdelmonem Mohamed Kozae,
Mohamed Shokry,
Manar Omran
Issue:
Volume 9, Issue 5, October 2020
Pages:
146-154
Received:
14 July 2020
Accepted:
3 August 2020
Published:
3 September 2020
Abstract: Intuitionistic Fuzzy set (IFS) theory plays an important role in real life and engineering problems. There are many model involving fuzzy matrices to deal with different complicated aspects. Intuitionistic fuzzy set (IFS) is useful in providing a flexible model for developing the uncertainty and vagueness involved in making decisions where the theories of uncertainty are very useful to treat with mathematics that needs to address. In other words, the application of intuitionistic fuzzy sets instead of fuzzy sets means the introduction of another degree of freedom into a set description. Intuitionistic fuzzy set (IFS) called the generalization of fuzzy sets was proposed in K. T. Atanassov. So, we can use it in decision making. We examined the definition of IFS and puts new definitions of IFS (Intuitionistic fuzzy set) in this paper and suggested its implementation in the Corona Covid-19. For several similar real-life cases the suggested approach can be applied.
Abstract: Intuitionistic Fuzzy set (IFS) theory plays an important role in real life and engineering problems. There are many model involving fuzzy matrices to deal with different complicated aspects. Intuitionistic fuzzy set (IFS) is useful in providing a flexible model for developing the uncertainty and vagueness involved in making decisions where the theo...
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Exploiting Machine Learning Algorithms for Predicting Crash Injury Severity in Yemen: Hospital Case Study
Tariq Al-Moqri,
Xiao Haijun,
Jean Pierre Namahoro,
Eshrak Naji Alfalahi,
Ibrahim Alwesabi
Issue:
Volume 9, Issue 5, October 2020
Pages:
155-164
Received:
27 August 2020
Accepted:
14 September 2020
Published:
28 September 2020
Abstract: This study focused on exploiting machine learning algorithms for classifying and predicting injury severity of vehicle crashes in Yemen. The primary objective is to assess the contribution of the leading causes of injury severity. The selected machine learning algorithms compared with traditional statistical methods. The filtrated second data collected within two months (August-October 2015) from the two main hospitals included 156 injured patients of vehicle crashes reported from 128 locations. The data classified into three categories of injury severity: Severe, Serious, and Minor. It balanced using a synthetic minority oversampling technique (SMOTE). Multinomial logit model (MNL) compared with five machine learning classifiers: Naïve Bayes (NB), J48 Decision Tree, Random Forest (RF), Support Vector Machine (SVM), and Multilayer Perceptron (MLP). The results showed that most of machine learning-based algorithms performed well in predicting and classifying the severity of the traffic injury. Out of five classifiers, RF is the best classifier with 94.84% of accuracy. The characteristics of road type, total injured person, crash type, road user, transport way to the emergency department (ED), and accident action were the most critical factors in the severity of the traffic injury. Enhancing strategies for using roadway facilities may improve the safety of road users and regulations.
Abstract: This study focused on exploiting machine learning algorithms for classifying and predicting injury severity of vehicle crashes in Yemen. The primary objective is to assess the contribution of the leading causes of injury severity. The selected machine learning algorithms compared with traditional statistical methods. The filtrated second data colle...
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Age-Infection Model and Control of Marek Disease
Uwakwe Joy Ijeoma,
Inyama Simeon Chioma,
Omame Andrew
Issue:
Volume 9, Issue 5, October 2020
Pages:
165-174
Received:
22 June 2020
Accepted:
7 July 2020
Published:
12 October 2020
Abstract: We formulated three compartmental model of Marek Disease model. We first determined the basic Reproduction number and the existence of Steady (Equilibrium) states (disease-free and endemic). Conditions for the local stability of the disease-free and endemic steady states were determined. Further, the Global stability of the disease-free equilibrium (DFE) and endemic equilibrium were proved using Lyponav method. We went further to carry out the sensitivity analysis or parametric dependence on R0 and later formulated the optimal control problem. We finally looked at numerical Results on poultry productivity in the presence of Marek disease and we drew five graphs to demonstrate this. The first figure shows the effect of both vaccination (v) and biosecurity measures (u) on the latently infected birds. The population of infected birds increases speedily and then remains stable without the application of any control measure, with the controls, the population increases to about 145 and then begins to reduce from day 8 till it drops to 50 on day 20 and then remains stable. With this strategy, only bird vaccination (v) is applied to control the system while the other control is set to zero. In the second figure, the effect of bird vaccination and its’ positive impact is revealed, though there is an increase to about 160 before a decrease occurs. From the third figure, as the control (u) ranges from 0.2 to 0.9, we see that the bird population still has a high level of latently infected birds. This result from figure shows that the bird population is not free from the disease, hence, the biosecurity control strategy is not effective without vaccination of susceptible birds and hence it is not preferable as the only control measure for marek disease. The numerical result in the fourth figure shows that as the latently infected bird population increases without control, with vaccination it decreases as more susceptible birds are vaccinated. From the fifth figure we observe, that as the control parameter increases, the total deaths by infection reduces, also as the age of the infection increases to the maximum age of infection which is 6 months (thatis, T=24 weeks), the number of deaths increases to 30 in a day. Hence, control measures should be applied at the early ages of infection in order to avoid high mortality rate during the outbreak of the disease.
Abstract: We formulated three compartmental model of Marek Disease model. We first determined the basic Reproduction number and the existence of Steady (Equilibrium) states (disease-free and endemic). Conditions for the local stability of the disease-free and endemic steady states were determined. Further, the Global stability of the disease-free equilibrium...
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