Ti6Al4V alloy is widely used in aerospace and medical applications. It is classified as a difficult to machine material due to its low thermal conductivity and high chemical reactivity. In this study, hybrid intelligent models have been developed to predict surface roughness when end milling Ti6Al4V alloy with a Physical Vapor Deposition PVD coated tool under dry cutting conditions. Back propagation neural network (BPNN) has been hybridized with two heuristic optimization techniques, namely: gravitational search algorithm (GSA) and genetic algorithm (GA). Taguchi method was used with an L27 orthogonal array to generate 27 experiment runs. Design expert software was used to do analysis of variances (ANOVA). The experimental data were divided randomly into three subsets for training, validation, and testing the developed hybrid intelligent model. ANOVA results revealed that feed rate is highly affected by the surface roughness followed by the depth of cut. One-way ANOVA, including a Post-Hoc test, was used to evaluate the performance of three developed models. The hybrid model of Artificial Neural Network-Gravitational Search Algorithm (ANN-GSA) has outperformed Artificial Neural Network (ANN) and Artificial Neural Network-Genetic Algorithm (ANN-GA) models. ANN-GSA achieved minimum testing mean square error of 7.41 × 10−13 and a maximum R-value of 1. Further, its convergence speed was faster than ANN-GA. GSA proved its ability to improve the performance of BPNN, which suffers from local minima problems.
Artificial roughness applied to a Solar Air Heater (SAH) absorber plate is a popular technique for increasing its total thermal efficiency (ηt−th). In this paper, the influence of geometrical parameters of V-down ribs attached below the corrugated absorbing plate of a SAH on the ηt−th was examined. The impacts of key roughness parameters, including relative pitch p/e (6–12), relative height e/D (0.019–0.043), angles of attack α (30–75°), and Re (1000–20,000), were examined under real weather conditions. The SAH ηt−th roughened by V-down ribs was predicted using an in-house developed conjugate heat-transfer numerical model. The maximum SAH ηt−th was shown to be 78.8% as predicted under the steady-state condition
... Show MoreThe fuzzy assignment models (FAMs) have been explored by various literature to access classical values, which are more precise in our real-life accomplishment. The novelty of this paper contributed positively to a unique application of pentagonal fuzzy numbers for the evaluation of FAMs. The new method namely Pascal’s triangle graded mean (PT-GM) has presented a new algorithm in accessing the critical path to solve the assignment problems (AP) based on the fuzzy objective function of minimising total cost. The results obtained have been compared to the existing methods such as, the centroid formula (CF) and centroid formula integration (CFI). It has been demonstrated that operational efficiency of this conducted method is exquisitely deve
... Show MoreThe fuzzy assignment models (FAMs) have been explored by various literature to access classical values, which are more precise in our real-life accomplishment. The novelty of this paper contributed positively to a unique application of pentagonal fuzzy numbers for the evaluation of FAMs. The new method namely Pascal's triangle graded mean (PT-GM) has presented a new algorithm in accessing the critical path to solve the assignment problems (AP) based on the fuzzy objective function of minimising total cost. The results obtained have been compared to the existing methods such as, the centroid formula (CF) and centroid formula integration (CFI). It has been demonstrated that operational efficiency of this conducted method is exquisitely develo
... Show MoreIn this research, Artificial Neural Networks (ANNs) technique was applied in an attempt to predict the water levels and some of the water quality parameters at Tigris River in Wasit Government for five different sites. These predictions are useful in the planning, management, evaluation of the water resources in the area. Spatial data along a river system or area at different locations in a catchment area usually have missing measurements, hence an accurate prediction. model to fill these missing values is essential.
The selected sites for water quality data prediction were Sewera, Numania , Kut u/s, Kut d/s, Garaf observation sites. In these five sites models were built for prediction of the water level and water quality parameters.
COVID 19 has spread rapidly around the world due to the lack of a suitable vaccine; therefore the early prediction of those infected with this virus is extremely important attempting to control it by quarantining the infected people and giving them possible medical attention to limit its spread. This work suggests a model for predicting the COVID 19 virus using feature selection techniques. The proposed model consists of three stages which include the preprocessing stage, the features selection stage, and the classification stage. This work uses a data set consists of 8571 records, with forty features for patients from different countries. Two feature selection techniques are used in
Crime is considered as an unlawful activity of all kinds and it is punished by law. Crimes have an impact on a society's quality of life and economic development. With a large rise in crime globally, there is a necessity to analyze crime data to bring down the rate of crime. This encourages the police and people to occupy the required measures and more effectively restricting the crimes. The purpose of this research is to develop predictive models that can aid in crime pattern analysis and thus support the Boston department's crime prevention efforts. The geographical location factor has been adopted in our model, and this is due to its being an influential factor in several situations, whether it is traveling to a specific area or livin
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The research aims to identify tax exemptions, their objectives and types, as well as to shed light on the concept of sustainable development, its objectives, dimensions and indicators (economic, social and environmental), as well as to analyze the relationship between tax exemptions and economic development, in addition to measuring and analyzing the impact of tax exemptions on economic development in Iraq for the period ( 2015 - 2021) using the NARDL model. The research problem centers on the fact that failure to employ financial policy tools correctly led to a weakness in achieving economic justice, which leads to a failure to improve social welfar
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