Authors:Uchenna IGBOELİ Abstract: A Polynomial Genetic Algorithm (PGA) is a type of evolutionary algorithm used for optimization problems that involve finding the minimum or maximum of a polynomial function. The algorithm is based on the principles of natural selection and genetic recombination and mutation. The algorithm starts by initializing a random population of chromosomes. The fitness of each chromosome is evaluated based on the value of the polynomial function it represents. The fittest chromosomes are selected for reproduction, and their genetic material is combined through crossover and mutation to produce a new generation of chromosomes. One important consideration in using a genetic algorithm for polynomial optimization is the choice of representation for the chromosomes. Binary or integer representations can be used, with each bit or integer representing a coefficient in the polynomial. Alternatively, a floating-point representation can be used, with each chromosome representing a set of coefficients that can be used to construct the polynomial.In summary, to solve a polynomial using a genetic algorithm, we need to define a fitness function that evaluates the fitness of each chromosome based on its ability to represent a good solution to the polynomial, and then use standard genetic algorithm techniques to evolve a population of chromosomes towards a solution. The solution found in this paper shows that though genetic algorithm can be used to solve polynomials, other methods like Newton-Ralpson, Secant, Regula-falsi and Bisection can easily guess the solution in a few iterations thereby saving cost and time PubDate: Mon, 03 Jul 2023 00:00:00 +030
Authors:Obalowa JOB; İbrahim ABDULLAHİ Abstract: This article's main emphasis was on the Nakagami Frechet (NF) distribution's generalization. In this study, theoretical derivations for the probability density function (PDF), cumulative distribution function (CDF), survival, and hazard functions of the NF distribution were derived and discussed. Some fundamental mathematical and statistical properties are derived. In addition, the maximum likelihood estimator is used to obtain the model parameters. We present the simulation to evaluate the reliability of maximum likelihood estimators. Finally, to demonstrate the utility of the proposed distribution, the model was applied to real-life data sets. PubDate: Mon, 03 Jul 2023 00:00:00 +030
Authors:Bayram KILIÇ Abstract: In this study, the energy analysis of the vapor compression refrigeration system (VCRS) using R417B was made for different operating conditions. The thermodynamic data required for the calculations were taken from the Coolpack program. In the analysis made depending on the evaporator temperature change, the highest COP value of the cycle is 4.5. This value was obtained under the operating condition of -1 oC evaporator temperature and 35 oC condenser temperature. It is thought that it would be beneficial to use the working conditions determined in this study in order to benefit effectively from the VCRS using R417B. PubDate: Mon, 03 Jul 2023 00:00:00 +030
Authors:Bayram KILIÇ; Bilge KEÇİCİ Abstract: Today, approximately 95% of the energy consumed for transportation all over the world is met by engines using hydrocarbon fuels. Accordingly, approximately 20% of global greenhouse gases are produced by the combustion of fuels used in transportation. CO2, CH4 and N2O are the most important greenhouse gas emissions from transportation. The identification, monitoring, control and reduction of greenhouse gases from transportation have a significant impact on global climate change. In this study, the greenhouse gas emissions from transportation in Turkey were evaluated. For this purpose, greenhouse gas emissions measured between 1990-2019 were used. Emission values are taken from the data of the Turkish Statistical Institute (TUIK). CO2 emissions from transportation in Turkey have increased every year since 1990. CH4 emissions from transportation have increased since 2000 and have recently reached their highest values. N2O emissions from transportation showed a small increase, and followed a stagnant course for long years. PubDate: Mon, 03 Jul 2023 00:00:00 +030
Authors:Stephen DUROWAYE; Haruna MUHAMMAD, Ganiyu LAWAL Abstract: The influence of desert date (Balanites Aegyptiacus) shell particulates on the physical and mechanical characteristics of aluminium matrix composites was studied. Desert date-shell particulates in varied weight percentages were added to molten A356 alloy by stir casting method for the production of the composites. The microstructure of the specimens produced was examined using optical and scanning electron microscopes. Furthermore, physical (density) and mechanical properties (tensile strength, hardness, and impact energy) were evaluated at room temperature. The composition of desert date-shell particulates was determined using an X-ray fluorescence (XRF) spectrometer. The result confirmed SiO2, to be the major constituent of the desert date (Balanites Aegyptiacus) shell particulates while Al2O3, CaO, Fe2O3, MgO, and minor oxides were in traces. The microstructure revealed networks of eutectic Si and precipitates of Mg2Si inter metallic compound in α-A356 matrix with desert dates shell particulates. It also revealed the particle sizes, particles distribution in the matrix and grain boundaries and good bonding of the particulates with the alloy matrix. The density of the composites decreased continuously with increase in desert date shell particles additions. The composite containing 115-µm particulates exhibited the highest tensile strength of 182.52 MPa at 9 wt. % reinforcement, which is 18 % higher than that of the unreinforced cast A356 alloy. It exhibited the highest hardness 85.59 HVF at 12 wt. % reinforcement, which is 22 % higher than that of the unreinforced cast A356 alloy. The composites demonstrated a progressive reduction in impact energy as reinforcement increased. PubDate: Mon, 03 Jul 2023 00:00:00 +030
Open Access journal
