Simulated annealing (SA) has been an effective means that can address difficulties related to optimization problems. is now a common discipline for research with several productive applications such as production planning. Due to the fact that aggregate production planning (APP) is one of the most considerable problems in production planning, in this paper, we present multi-objective linear programming model for APP and optimized by . During the course of optimizing for the APP problem, it uncovered that the capability of was inadequate and its performance was substandard, particularly for a sizable controlled problem with many decision variables and plenty of constraints. Since this algorithm works sequentially then the current state wi

This study involved the effect of anew nickel (II) complexs with formla [NiL2(H2O)2].2.5ETOH where L=Bis[5-(p-nitrophenyL)-4-phenyL-1,2,4-traizole-3-dithocarbamato hydrazide] diaqua. nickel(II). Ethanol(2.5).and anti-cancer drug cyclophosphamide on specific actifity of two Liver enzymes (GOT,GPT) in the (Liver,kidney) tissues and on the creatinine Level in the kidney byUtilizing an invivosystem in femalmice.The result showed that inhibition in the activity of GPT and GOT enzymes in theLiver and in both nickel (II) complex and cyclophosphamide drug (CP) . mice weretreated with three doses (90,180,320) µg/mouse for three days for each group.The Liver show's the highest rate of GPT inhibition was about 97.43% at180µg/mouse regarding the ki

The aim of this paper is to approximate multidimensional functions by using the type of Feedforward neural networks (FFNNs) which is called Greedy radial basis function neural networks (GRBFNNs). Also, we introduce a modification to the greedy algorithm which is used to train the greedy radial basis function neural networks. An error bound are introduced in Sobolev space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result is published in [16]).

In this study, the behavior of screw piles models with continuous helix was studied by conducting laboratory experimental tests on a single screw pile that has several aspect ratios (L/D) under the influence of static axial compression loads. The screw piles were inserted in a soft soil that has a unit weight of 18.72 kN/m3 and moisture content of 30.19%. Also, the soil has a liquid limit of 55% and a plasticity index of 32%. A physical laboratory model was designed to investigate the ultimate compression capacity of the screw pile and measure the generated porewater pressure during the loading process. The bedding soil was prepared according to the field unit weight and moisture content and the failure load was assumed correspondin

The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet