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.
This study presents the multi criteria single-machine model. The machine scheduling problem (MSP) for ntasks on a single machine involves minimizing a function of three criteria: total completion time (C_j),maximum earliest (E_max), and tardiness (〖ΣT〗_j), This is an NP-hard issue. Within this work's theoretical section, we present the mathematical formulation of The presented topic thenhighlights the usefulness of the dominance rule (DR), which may be used to develop effective solutions. Whilein the practical part, one of the important exact methods; The proposed MSP tricriteria are solved by applyingthe Branch and Bound (BAB) method, which finds a set of efficient solutions for 1//F(ΣC_j ,ΣT_j ,E_max) upto n=100 jobs. The BAB appro
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Under the state scenario, fiscal policy will not be able to use the oil surpluses optimally and economically and society, as long as these surpluses are not directed by public expenditure towards new productive investments and by following the path of fiscal policy after one year 2003 and until 2013 we note that it is based on the method of spending (excessive) consumption, and did not take any action towards the budget deficit planned at the beginning of the fiscal year, and the actual surplus at the end of the fiscal year, which represents the highest expenditure in the budget, Salaries and wages of workers in various government agencies with the expansion of spending on the security side.&n
... Show MoreTourism is a human phenomenon and economic and social activity. It represents an effective forces in the life of the individuals and state alike. As any other economic and human activity has appositive and negative results.
So there is a necessary to planning and activate this sector to get the most possible advantage.
Tourism has special importance out of its effect on the structure and performance of national economy. It can be regarded a dynamic activity with mutual effect include all the economic activities within and out the state. Tourism is affected and affect the production con summing , joineries , communication , ports ,hotel , restaurants ,internal and
... Show MoreThe implementation of decentralization in Iraq was asymmetrical, leading to different forms and paces of implementation. Comparing four cases of Basra, Kirkuk, Nineveh, and Sulaymaniyah indicate that these cases differ in their political stability and autonomy in a way that led to a different forms of decentralization. This paper argues that the higher the level of political autonomy from the federal government, the more efficient the governance model, and the more efficient the governance model, the more legitimate the system (trust), and the more legitimate a system, the more accountable elected officials. Therefore, it recommends reforming the institutional setup of decentralization by having districts, instead of provinces, as the bu
... Show MoreThe photooxidative degradation process of plastics caused by ultraviolet irradiation leads to bond breaking, crosslinking, the elimination of volatiles, formation of free radicals, and decreases in weight and molecular weight. Photodegradation deteriorates both the mechanical and physical properties of plastics and affects their predicted life use, in particular for applications in harsh environments. Plastics have many benefits, while on the other hand, they have numerous disadvantages, such as photodegradation and photooxidation in harsh environments and the release of toxic substances due to the leaching of some components, which have a negative effect on living organisms. Therefore, attention is paid to the design and use of saf
... Show MoreThe current study suggested a thermal treatment as a necessary proactive step in improving the adsorption capacity of bio-waste for contaminants removal in wastewater. This approach was based on the experimental and histological investigation of biowaste pods shell. This investigation showed that these shells compose of parenchyma cells that store secondary metabolites compounds produced from cells were exhibited in present study. The results also reported that these compounds are extracted directly from the cells as soon as they are exposed to an aqueous solution, hampering their use as an adsorbent material. The increase in the weight of bio-waste adsorbent at unit liquid volume increases the production of secondary metabolites compounds
... Show MoreIn the field of civil engineering, the adoption and use of Falling Weight Deflectometers (FWDs) is seen as a response to the ever changing and technology-driven world. Specifically, FWDs refer to devices that aid in evaluating the physical properties of a pavement. This paper has assessed the concepts of data processing, storage, and analysis via FWDs. The device has been found to play an important role in enabling the operators and field practitioners to understand vertical deflection responses upon subjecting pavements to impulse loads. In turn, the resultant data and its analysis outcomes lead to the backcalculation of the state of stiffness, with initial analyses of the deflection bowl occurring in conjunction with the measured or assum
... Show More<span lang="EN-US">The need for robotics systems has become an urgent necessity in various fields, especially in video surveillance and live broadcasting systems. The main goal of this work is to design and implement a rover robotic monitoring system based on raspberry pi 4 model B to control this overall system and display a live video by using a webcam (USB camera) as well as using you only look once algorithm-version five (YOLOv5) to detect, recognize and display objects in real-time. This deep learning algorithm is highly accurate and fast and is implemented by Python, OpenCV, PyTorch codes and the Context Object Detection Task (COCO) 2020 dataset. This robot can move in all directions and in different places especially in
... Show MoreManufacturing industry is constantly looking for ways to improve the efficiency of production processes so as to lower production costs, maintain product quality, and improve production planning. This study aims to provide an integrated optimization and forecasting framework that combines Cutting Optimization Pro5, linear programming, and an Enhanced N-BEATS deep learning model to minimize material waste and manufacturing cost and to predict the number of production items with a price-reduction strategy. The real industrial case study is based on production and pricing data from the Akad factory of the General Company for Electrical and Electronic Products in Iraq for the period from 2014 to 2025, concerning the manufacture of 80 L
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