approximation model
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2021 ◽  
pp. 1-11
Author(s):  
Jie Yang ◽  
Tian Luo ◽  
Lijuan Zeng ◽  
Xin Jin

Neighborhood rough sets (NRS) are the extended model of the classical rough sets. The NRS describe the target concept by upper and lower neighborhood approximation boundaries. However, the method of approximately describing the uncertain target concept with existed neighborhood information granules is not given. To solve this problem, the cost-sensitive approximation model of the NRS is proposed in this paper, and its related properties are analyzed. To obtain the optimal approximation granular layer, the cost-sensitive progressive mechanism is proposed by considering user requirements. The case study shows that the reasonable granular layer and its approximation can be obtained under certain constraints, which is suitable for cost-sensitive application scenarios. The experimental results show that the advantage of the proposed approximation model, moreover, the decision cost of the NRS approximation model will monotonically decrease with granularity being finer.


2021 ◽  
Vol 5 (S4) ◽  
Author(s):  
Kateryna I. Kotsiubivska ◽  
Olena V. Tymoshenko ◽  
Olena A. Chaikovska ◽  
Maryna S. Tolmach ◽  
Svitlana S. Khrushch

The article considers methodological approaches to assessing the level of development of economic systems in the context of increasing the accuracy of forecasts in unpredictable socio-economic conditions in particular taking into account the impact of unforeseen environmental risks and disasters. The authors used methods to approximate economic criteria with the help of neural networks. Analyzing the criteria of economic development of different countries, as well as taking into account the factors of the macroeconomic environment, a neural network approximation model of risk forecasting in the economic development of the country has been developed. To date, a large number of mathematical forecasting methods are known, and experts in the world economy use appropriate risk assessment criteria, but the neural network is used when the exact type of connections between inputs and outputs is unknown, which allows us to create a more accurate and flexible forecast model. The modeling takes into account the main weights that determine the degree and the priority of the impact on each component of the economic system and characterizes the complex macroeconomic relationships to determine the aggregate indices.


2021 ◽  
Vol 408 ◽  
pp. 126342
Author(s):  
Jie Lin ◽  
Ting-Zhu Huang ◽  
Xi-Le Zhao ◽  
Tian-Hui Ma ◽  
Tai-Xiang Jiang ◽  
...  

2021 ◽  
Vol 9 (4) ◽  
pp. 852-859
Author(s):  
Clement Ayarebilla Ali ◽  

The study compared exhaustively the Successive Approximation Model (SAM) and Analyze, Design, Develop, Implement and Evaluate (ADDIE) model on the teaching and learning of Science, Technology, Engineering and Mathematics subjects in Ghana. We selected a sample of 30 student-teachers who offered Mathematics and Science in the distance mode of the University of Education, Winneba, Ghana in the 2018/2019 academic year. The first stage of the analysis compared the models separately within the Vygotskian framework using pre-post experiemtal design. The second stage made comparisons between and within the two models. The results of both stages showed that student-teachers preferred mostly SAM to ADDIE instructional models. There were not only consistently higher mean gains in the latter model, but the group averages of student-teachers in the post-treatment results also demonstrated clear improvements. Again, student-teachers showed tremendous improvements in the conceptual understanding of both models. However, the Successive Approximation Model recorded much more improvements in both pre-treatment and post-treatment results. It was therefore imperative to conclude that the Successive Approximation Model was more properly situated in the context of teaching and learning Mathematics and Science. We, therefore, recommended experimental explorations of SAM for STEM.


2021 ◽  
Vol 9 (4) ◽  
pp. 852-859
Author(s):  
Clement Ayarebilla Ali ◽  

The study compared exhaustively the Successive Approximation Model (SAM) and Analyze, Design, Develop, Implement and Evaluate (ADDIE) model on the teaching and learning of Science, Technology, Engineering and Mathematics subjects in Ghana. We selected a sample of 30 student-teachers who offered Mathematics and Science in the distance mode of the University of Education, Winneba, Ghana in the 2018/2019 academic year. The first stage of the analysis compared the models separately within the Vygotskian framework using pre-post experiemtal design. The second stage made comparisons between and within the two models. The results of both stages showed that student-teachers preferred mostly SAM to ADDIE instructional models. There were not only consistently higher mean gains in the latter model, but the group averages of student-teachers in the post-treatment results also demonstrated clear improvements. Again, student-teachers showed tremendous improvements in the conceptual understanding of both models. However, the Successive Approximation Model recorded much more improvements in both pre-treatment and post-treatment results. It was therefore imperative to conclude that the Successive Approximation Model was more properly situated in the context of teaching and learning Mathematics and Science. We, therefore, recommended experimental explorations of SAM for STEM.


2021 ◽  
pp. 245-254
Author(s):  
Marta Kosior-Kazberuk ◽  
Dmytro Kochkarev ◽  
Taliat Azizov ◽  
Tatiana Galinska

2021 ◽  
Vol 9 (9) ◽  
pp. 941
Author(s):  
Sarat Chandra Mohapatra ◽  
C. Guedes Soares

A boundary integral equation method (BIEM) model for the problem of surface wave interaction with a moored finite floating flexible plate is presented. The BIEM solution is obtained by employing the free surface Greens function and Green’s theorem, and the expressions for the plate deflection, reflection, and transmission coefficients are derived from the integro-differential equation. Furthermore, the shallow water approximation model and its solution is obtained based on the matching technique in a direct manner. The accuracy of the present BIEM code is checked by comparing the results of deflection amplitude, reflection, and transmission coefficients with existing published results and experimental datasets as well as the shallow water approximation model. The hydroelastic response of the moored floating flexible plate is studied by analyzing the effects of the mooring stiffness, incidence angle, and flexural rigidity on the deflection amplitude, plate deformations, reflection, and transmission coefficients. The present analysis may be helpful in understanding the different physical parameters to model a wave energy conversion device with mooring systems over BIEM formulations.


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