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 aimed to identify the role of school administration in achieving educational and learning goals from the point of view of educational supervisors in the stage of basic education. The descriptive method was adopted. As for the sample size, it has reached (59) educational supervisors. A questionnaire consisting of 29 paragraphs divided into four areas was used. The data were statistically analyzed on the Chi-square test, the percentage, and the mono-variance analysis. The result showed that the school administration contributes to achieving educational goals. It also works to solve problems in democratic ways, and in modern methods, there are differences in the criteria for choosing the headmaster. The study recommended that sch
... Show MoreIf the sovereignty of the state is reflected in the taxation of its citizens, this sovereignty can not be completed and completed only if it works on its part to collect its debts, whether voluntary or compulsory, and the debt of the debt arises from the will of the individual and the will of the state alone, The existing management of seizure and collection is based on an unequal relationship between the State and the debtor from which the obligation arises. Naturally, this relationship has obligations and rights on both parties. The researcher used a set of studies and previous research, books and other sources related to the subject of research. This was done through the theoretical and practical aspects, which focused on direct and i
... Show MoreThis research includes the application of non-parametric methods in estimating the conditional survival function represented in a method (Turnbull) and (Generalization Turnbull's) using data for Interval censored of breast cancer and two types of treatment, Chemotherapy and radiation therapy and age is continuous variable, The algorithm of estimators was applied through using (MATLAB) and then the use average Mean Square Error (MSE) as amusement to the estimates and the results showed (generalization of Turnbull's) In estimating the conditional survival function and for both treatments ,The estimated survival of the patients does not show very large differences
... Show MoreThe analysis of time series considers one of the mathematical and statistical methods in explanation of the nature phenomena and its manner in a specific time period.
Because the studying of time series can get by building, analysis the models and then forecasting gives the priority for the practicing in different fields, therefore the identification and selection of the model is of great importance in spite of its difficulties.
The selection of a standard methods has the ability for estimation the errors in the estimated the parameters for the model, and there will be a balance between the suitability and the simplicity of the model.
In the analysis of d
... Show MoreAA wahid, journal mustansiriyah of sports science, 2023
This study sought to investigate the impacts of big data, artificial intelligence (AI), and business intelligence (BI) on Firms' e-learning and business performance at Jordanian telecommunications industry. After the samples were checked, a total of 269 were collected. All of the information gathered throughout the investigation was analyzed using the PLS software. The results show a network of interconnections can improve both e-learning and corporate effectiveness. This research concluded that the integration of big data, AI, and BI has a positive impact on e-learning infrastructure development and organizational efficiency. The findings indicate that big data has a positive and direct impact on business performance, including Big
... Show MoreA batch and flow injection (FI) spectrophotometric methods are described for the determination of barbituric acid in aqueous and urine samples. The method is based on the oxidative coupling reaction of barbituric acid with 4-aminoantipyrine and potassium iodate to form purple water soluble stable product at λ 510 nm. Good linearity for both methods was obtained ranging from 2 to 60 μg mL−1, 5–100 μg mL−1 for batch and FI techniques, respectively. The limit of detection (signal/noise = 3) of 0.45 μg mL−1 for batch method and 0.48 μg mL−1 for FI analysis was obtained. The proposed methods were applied successfully for the determination of barbituric acid in tap water, river water, and urine samples with good recoveries of 99.92
... Show MoreThe objective of the present study is to determine the nature and direction of the correlation between mathematical excellence and learning styles as defined by the Entwistle, model in fifth-grade scientific female students. The descriptive correlational approach was implemented by the two researchers to accomplish the research objectives. A scale was developed to assess the learning styles of female students in the sample in accordance with the Entwistle, model. : (Knowledge, understanding, application, analysis, synthesis, evaluation, systematic thinking, creativity), and the research community was determined by the female students of the scientific fifth grade in the morning preparatory and secondary schools of the General Direct
... Show MoreA three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an
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