Currently, one of the topical areas of application of machine learning methods is the prediction of material characteristics. The aim of this work is to develop machine learning models for determining the rheological properties of polymers from experimental stress relaxation curves. The paper presents an overview of the main directions of metaheuristic approaches (local search, evolutionary algorithms) to solving combinatorial optimization problems. Metaheuristic algorithms for solving some important combinatorial optimization problems are described, with special emphasis on the construction of decision trees. A comparative analysis of algorithms for solving the regression problem in CatBoost Regressor has been carried out. The object of the study is the generated data sets obtained on the basis of theoretical stress relaxation curves. Tables of initial data for training models for all samples are presented, a statistical analysis of the characteristics of the initial data sets is carried out. The total number of numerical experiments for all samples was 346020 variations. When developing the models, CatBoost artificial intelligence methods were used, regularization methods (Weight Decay, Decoupled Weight Decay Regularization, Augmentation) were used to improve the accuracy of the model, and the Z-Score method was used to normalize the data. As a result of the study, intelligent models were developed to determine the rheological parameters of polymers included in the generalized non-linear Maxwell-Gurevich equation (initial relaxation viscosity, velocity modulus) using generated data sets for the EDT-10 epoxy binder as an example. Based on the results of testing the models, the quality of the models was assessed, graphs of forecasts for trainees and test samples, graphs of forecast errors were plotted. Intelligent models are based on the CatBoost algorithm and implemented in the Jupyter Notebook environment in Python. The constructed models have passed the quality assessment according to the following metrics: MAE, MSE, RMSE, MAPE. The maximum value of model error predictions was 0.86 for the MAPE metric, and the minimum value of model error predictions was 0.001 for the MSE metric. Model performance estimates obtained during testing are valid.
Two nanocomposite corrosion inhibitors were synthesized from Aloe vera extract: one incorporating sodium thiosulfate and the other silver nitrate. Both nanocomposites were subjected to structural characterization using atomic force microscopy (AFM), which revealed distinct morphological features. The sodium thiosulfate-based nanocomposite exhibited uniform and well-dispersed nanoparticles with an average size of 47.51 nm, suggesting a stable and homogeneous distribution. In contrast, the silver nitrate-based nanocomposite displayed slightly larger particles with an average diameter of 58.34 nm, indicating a tendency toward moderate aggregation. The corrosion inhibition performance of these nanocomposites for carbon steel (CS1137) was invest
... Show MoreVisualization of water flow around different bluff bodies at different Reynolds number ranging (1505 - 2492) was realized by designing and building a test rig which contains an open channel capable to ensure water velocity range (4-8cm/s) in this channel. Hydrogen bubbles generated from the ionized water using DC power supply are visualized by a light source and photographed by a digital camera. Flow pattern around a circular disk of (3.6cm) diameter and (3mm) thickness, a sphere of (3.8cm) diameter and a cylinder of
(3.2cm) diameter and (10cm) length are studied qualitatively. Parameters of the vortex ring generated in the wake region of the disk and the separation angle of water stream lines from the surface of the sphere are plott
Each organization struggles to exploit each possible opportunity for gaining success and continuing with its work carrier. In this field, organization success can be concluded by fulfilling end user requirements combined with optimizing available resources usage within a specified time and acceptable quality level to gain maximum profit. The project ranking process is governed by the multi-criteria environment, which is more difficult for the governmental organization because other organizations' main target is maximizing profit constrained with available resources. The governmental organization should consider human, social, economic and many more factors. This paper focused on building a multi-criteria optimizing proje
... Show MoreImage segmentation using bi-level thresholds works well for straightforward scenarios; however, dealing with complex images that contain multiple objects or colors presents considerable computational difficulties. Multi-level thresholding is crucial for these situations, but it also introduces a challenging optimization problem. This paper presents an improved Reptile Search Algorithm (RSA) that includes a Gbest operator to enhance its performance. The proposed method determines optimal threshold values for both grayscale and color images, utilizing entropy-based objective functions derived from the Otsu and Kapur techniques. Experiments were carried out on 16 benchmark images, which inclu
A reduced-order extended state observer (RESO) based a continuous sliding mode control (SMC) is proposed in this paper for the tracking problem of high order Brunovsky systems with the existence of external perturbations and system uncertainties. For this purpose, a composite control is constituted by two consecutive steps. First, the reduced-order ESO (RESO) technique is designed to estimate unknown system states and total disturbance without estimating an available state. Second, the continuous SMC law is designed based on the estimations supplied by the RESO estimator in order to govern the nominal system part. More importantly, the robustness performance is well achieved by compensating not only the lumped disturbance, but also its esti
... Show MoreThe world is keeping pace with evolution in all its fields as a result of scientists' pursuit of continuous scientific and technological development. This evolution included the sports field, which had a large space in the aspect of development and for all disciplines, Therefore, it's reflected today in what we see of records and advanced achievements in sporting events and activities. The development in the field of sports was the result of scientific research (Hussein and Jawad., 2022), where the interest in the training process has become one of the most important pillars of the development of achievement (Neamah and Altay., 2020). The shooting sport has also witnessed a remarkable development due to the diversity and development of its
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