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.
The study aims to identify the extent the academics in colleges of applied sciences are familiar with the themes of the national strategy of education 2040 in the Sultanate of Oman. The researchers used the descriptive approach, as well as they adopted a questionnaire with five dimensions as a tool for data collection, which was applied to (120) academics. The results showed that the academics of the applied colleges' familiarity with the National Strategy for Education 2040 in the Sultanate of Oman is average. The study also found that there were no statistically significant differences in the academics estimates of the extent of the Colleges of Applied Sciences academics’ familiarity with the themes of the National Education 2040 Str
... Show MoreBackground: Crohn's disease (CD) is an immunological disorder associated with chronic inflammatory process of several unspecific regions of gastrointestinal tract but frequently detected in the terminal Ilium and proximal colon or both. This disease frequently presented with various oral manifestations as a consequence of inflammatory process of the disease, nutritional deficiency or medications side effects. Several therapeutic approaches have been developed for CD management that are targeting the inflammatory process and directed at controlling the host immune response. Immunosuppressants such as Azathioprine and anti-TNF α agents as well as the combination of them have been widely used as an effective therapeutic modality with a bett
... Show MoreThe process of capital investment appraisal takes hold the attention of managers and accountants of the industrial companies. This process involves the use of multiple and diverse financial evaluation methods to measure the economic attractiveness of capital investment peojects. This multiplicity and diversity of financial evaluation metods have been the motive of this research to: investigate some organizational variables such as the desired objectives, identify managerial procedures which regulate the capital investment process, specify evaluation methods and examine the relationships between these variables and evaluation methods actually used by a sample of public industrial companies in Jordan.
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... Show MoreThe objective of present study was to compare of several methods for estimating the degree of heritability and calculating the number of genes using generation mean analysis of maize (
AbstractThe research aims to identify the impact of the different methods in calculating the Items sensitivity coefficient on the standard characteristics of the Criterion-Referenced test in the measurement and evaluation material. The research sample consisted of (35) male and female students, who were chosen by the intentional method. The researcher prepared learning-teaching program in constructing the content of the measurement and evaluation material for non-specialized departments, prepared an achievement test in its equivalent forms, identified the results of agreement between the methods used in analyzing the items of the criterion-referenced test, and compared the standard characteristics of the achievement test, both according to
... Show MoreThe effect of cognitive trips via the Internet (web quest) accompanying practical lessons in learning some basic handball skills for female students
BP algorithm is the most widely used supervised training algorithms for multi-layered feedforward neural net works. However, BP takes long time to converge and quite sensitive to the initial weights of a network. In this paper, a modified cuckoo search algorithm is used to get the optimal set of initial weights that will be used by BP algorithm. And changing the value of BP learning rate to improve the error convergence. The performance of the proposed hybrid algorithm is compared with the stan dard BP using simple data sets. The simulation result show that the proposed algorithm has improved the BP training in terms of quick convergence of the solution depending on the slope of the error graph.