<span>Dust is a common cause of health risks and also a cause of climate change, one of the most threatening problems to humans. In the recent decade, climate change in Iraq, typified by increased droughts and deserts, has generated numerous environmental issues. This study forecasts dust in five central Iraqi districts using machine learning and five regression algorithm supervised learning system framework. It was assessed using an Iraqi meteorological organization and seismology (IMOS) dataset. Simulation results show that the gradient boosting regressor (GBR) has a mean square error of 8.345 and a total accuracy ratio of 91.65%. Moreover, the results show that the decision tree (DT), where the mean square error is 8.965, comes in second place with a gross ratio of 91%. Furthermore, Bayesian ridge (BR), linear regressor (LR), and stochastic gradient descent (SGD), with mean square error and with accuracy ratios of 84.365%, 84.363%, and 79%. As a result, the performance precision of these regression models yields. The interaction framework was designed to be a straightforward tool for working with this paradigm. This model is a valuable tool for establishing strategies to counter the swiftness of climate change in the area under study.</span>
In this study, a new technique is considered for solving linear fractional Volterra-Fredholm integro-differential equations (LFVFIDE's) with fractional derivative qualified in the Caputo sense. The method is established in three types of Lagrange polynomials (LP’s), Original Lagrange polynomial (OLP), Barycentric Lagrange polynomial (BLP), and Modified Lagrange polynomial (MLP). General Algorithm is suggested and examples are included to get the best effectiveness, and implementation of these types. Also, as special case fractional differential equation is taken to evaluate the validity of the proposed method. Finally, a comparison between the proposed method and other methods are taken to present the effectiveness of the proposal meth
... Show MoreRoughness length is one of the key variables in micrometeorological studies and environmental studies in regards to describing development of cities and urban environments. By utilizing the three dimensions ultrasonic anemometer installed at Mustansiriyah university, we determined the rate of the height of the rough elements (trees, buildings and bridges) to the surrounding area of the university for a radius of 1 km. After this, we calculated the zero-plane displacement length of eight sections and calculated the length of surface roughness. The results proved that the ranges of the variables above are ZH (9.2-13.8) m, Zd (4.3-8.1) m and Zo (0.24-0.48) m.
Optimizing system performance in dynamic and heterogeneous environments and the efficient management of computational tasks are crucial. This paper therefore looks at task scheduling and resource allocation algorithms in some depth. The work evaluates five algorithms: Genetic Algorithms (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Firefly Algorithm (FA) and Simulated Annealing (SA) across various workloads achieved by varying the task-to-node ratio. The paper identifies Finish Time and Deadline as two key performance metrics for gauging the efficacy of an algorithm, and a comprehensive investigation of the behaviors of these algorithms across different workloads was carried out. Results from the experiment
... Show MorePhase change materials (PCMs) such as paraffin wax can be used to store or release large amount of energy at certain temperature at which their solid-liquid phase changes occurs. Paraffin wax that used in latent heat thermal energy storage (LHTES) has low thermal conductivity. In this study, the thermal conductivity of paraffin wax has been enhanced by adding different mass concentration (1wt.%, 3wt.%, 5wt.%) of (TiO2) nano-particles with about (10nm) diameter. It is found that the phase change temperature varies with adding (TiO2) nanoparticles in to the paraffin wax. The thermal conductivity of the composites is found to decrease with increasing temperature. The increase in thermal conductivity ha
... Show MoreContinuous escalation of the cost of generating energy is preceded by the fact of scary depletion of the energy reserve of the fossil fuels and pollution of the environment as developed and developing countries burn these fuels. To meet the challenge of the impending energy crisis, renewable energy has been growing rapidly in the last decade. Among the renewable energy sources, solar energy is the most extensively available energy, has the least effect on the environment, and is very efficient in terms of energy conversion. Thus, solar energy has become one of the preferred sources of renewable energy. Flat-plate solar collectors are one of the extensively-used and well-known types of solar collectors. However, the effectiveness of the coll
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