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.
Agricultural development occupies an important position in the economies of developing countries, and its role is greater for the Arab countries. The first task is to provide food security for all the population through sustainable development, which includes the investment of available natural resources and employment opportunities for the rural population, As well as the provision of raw materials for agricultural processing in order to increase agricultural exports to reduce the balance of payments deficit. Sustainable development is linked to increased production and improvement, as well as to food security. On the one hand, it has to cope with the increase in population and if it is possible to achieve a surplus allocated for export, a
... Show MorePurpose – The research aims to introduce sustainable agricultural development and the possibility of its application in the Iraqi agricultural sector by setting a proposed plan by which to overcome obstacles and then advance the reality of the agricultural sector in Iraq and the fact that the process of achieving agricultural development in the Iraqi agricultural sector today has become more sophisticated and more distant than before. The study adopted the descriptive analytical approach based on the principles of economic theory to clarify the shortcomings in the process of harmony between the three main elements of sustainable agricultural development, which are natural, social, and manufactured.
... Show MoreFeed Forward Back Propagation artificial neural network (ANN) model utilizing the MATLAB Neural Network Toolbox is designed for the prediction of surface roughness of Duplex Stainless Steel during orthogonal turning with uncoated carbide insert tool. Turning experiments were performed at various process conditions (feed rate, cutting speed, and cutting depth). Utilizing the Taguchi experimental design method, an optimum ANN architecture with the Levenberg-Marquardt training algorithm was obtained. Parametric research was performed with the optimized ANN architecture to report the impact of every turning parameter on the roughness of the surface. The results suggested that machining at a cutting speed of 355 rpm with a feed rate of 0.07 m
... Show MoreThis paper deals with prediction the effect of soil remoulding (smear) on the ultimate bearing capacity of driven piles. The proposed method based on detecting the decrease in ultimate bearing capacity of the pile shaft (excluding the share of pile tip) after sliding downward. This was done via conducting an experimental study on three installed R.C piles in a sandy clayey silt soil. The piles were installed so that a gap space is left between its tip and the base of borehole. The piles were tested for ultimate bearing capacity
according to ASTM D1143 in three stages. Between each two stages the pile was jacked inside the borehole until a sliding of about 200mm is achieved to simulate the soil remoulding due to actual pile driving. T
This paper deals with prediction the effect of soil re-moulding (smear) on the ultimate bearing capacity of driven piles. The proposed method based on detecting the decrease in ultimate bearing capacity of the pile shaft (excluding the share of pile tip) after sliding downward. This was done via conducting an experimental study on three installed R.C piles in a sandy clayey silt soil. The piles were installed so that a gap space is left between its tip and the base of borehole. The piles were tested for ultimate bearing capacity according to ASTM D1143 in three stages. Between each two stages the pile was jacked inside the borehole until a sliding of about 200mm is achieved to simulate the soil re-moulding due to actual pile driving. The re
... Show Moreobjective the research to diagnosis and interpretation of the nature of the correlation between the basic elements of knowledge management (tecgnology , structure , culture , process , human resource ) and the strategic performance of the Iraqi private banks, the research community and the level dimensions, and tested this research in the private banking sector represented by (7), especially in Baghdad city, Iraqi banks, and applied on sample consisting of 100 distributors in several administrative levels Director (Director, Director of the department, branch manager), and use questionnaire Head to collect data and information tool, and some private banks annual reports, has sought research to test a number of h
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