Application of parametric identification method and radial basis function networks for solution of inverse boundary value problems

Gorbachenko, Vladimir; Alqezweeni, Mohie M.; Jaafar, Mustafa Sadeq; Orbachenko, Valerievich Z.

doi:10.1109/ntict.2017.7976151

Cited by 3 publications

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“…If the model is developed in a standard way, on a finite set of parameter changes, a lot more calculations are required. Anecdotal evidence suggests [37][38][39][40][41][42][43][44][45][46][47][48][49] that applying neural networks appears to be more promising for such problems.…”

Section: Using Neural Network For the Simulation Of Physical Processmentioning

confidence: 99%

Developing a Model of Increasing the Learners’ Bilingual Professional Capacity in the Virtual Laboratory Environment

et al. 2020

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The article considers industrial applications of digital twins and their contribution to decision-making and prevention of failures in manufacturing. Virtual laboratories are described as an example of using digital twins not only in industry but also for educational purposes. The article is also focused on the value of physical and virtual investigations through the prism of content and language integrated learning approach (CLIL) and it offers recommendations for combining the two to strengthen science inquiry learning and job-relevant learning. Students conduct online investigations resulting in interdisciplinary team interaction and knowledge integration. Adopting the CLIL approach changes engineering students’ attitudes to learning a foreign language, drums up their academic interest, and strengthens their motivation. In addition, the article describes how neural networks are applied for the simulation of physical processes in a virtual laboratory. The advantages of using virtual laboratories for professional-oriented training include linking observable and unobservable phenomena, pointing out essential information, and providing online, adaptive guidance. To evaluate the efficiency of the virtual laboratory environment, we conducted an experiment to assess the effectiveness of an integrated learning course with the elements of a virtual laboratory. The sample was 48 students (23 of them were enrolled on the course based on integrated learning with elements of virtual environment; 25 students studied professional discipline and professional English separately). To collect the data two online testing on English were conducted. The professional discipline was evaluated once at the end of the semester. In addition, we conducted an online survey on motivation for students of both groups to reveal the influence of educational process organization on this indicator. The results of the experiment allowed us to ascertain that the CLIL approach in the virtual laboratory environment resulted in better outcomes and helped the students adopt a more positive attitude to learning English.

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Section: Using Neural Network For the Simulation Of Physical Processmentioning

confidence: 99%

Developing a Model of Increasing the Learners’ Bilingual Professional Capacity in the Virtual Laboratory Environment

et al. 2020

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Improving Algorithms for Learning Radial Basic Functions Networks to Solve the Boundary Value Problems

Gorbachenko

Savenkov

2020

Avatar-Based Control, Estimation, Communications, and Development of Neuron Multi-Functional Technology Platforms

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Digital twins are widely used in modern industry. A digital twin is a computer model that copies the behavior of a physical object. Digital twins of objects with distributed parameters are mathematically boundary value problems for partial differential equation. Traditionally, such problems are solved by finite difference and finite element methods, which require a complex grid construction procedure. The numerical solution of boundary value problems employs mesh less methods that do not require grid construction. Among mesh fewer methods, projection methods that use radial basis functions (RBFs) as basic functions are popular. Methods using RBF allow us to obtain a differentiable solution at any point in the solution domain, applicable to problems of arbitrary dimension with complex computational domains. When solving the problem, the parameters of the basic functions are selected, and the weights are calculated so that the residuals obtained after the substitution of the approximate solution at the test points in the equation are zero.

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Avatar-Based Natural Neural Network as a Dynamic Virtual Model

Veretekhina

Gorbachenko

2020

International Journal of Applied Research in Bioinformatics

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Avatar-based natural neural network (A-B Triple N) is widely used in modern industry created by Prof. Vardan Mkrttchian. The A-B Triple N is a dynamic virtual model of a system, process or service. The A-B Triple N continuously learns and updates its parameters, receiving information from a variety of sensors, correctly representing the state of a biophysical object. When learning, they use current data from sensors, control devices, and from the external bio environment combining actual data with the knowledge gained from specialists in this field. A-B Triple Ns allow you to monitor systems and processes in real time and analyze data in a timely manner to prevent problems before they occur, schedule preventive maintenance, reduces downtime, opens up new business opportunities and plans future updates and new developments.

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Application of parametric identification method and radial basis function networks for solution of inverse boundary value problems

Cited by 3 publications

References 0 publications

Developing a Model of Increasing the Learners’ Bilingual Professional Capacity in the Virtual Laboratory Environment

Developing a Model of Increasing the Learners’ Bilingual Professional Capacity in the Virtual Laboratory Environment

Improving Algorithms for Learning Radial Basic Functions Networks to Solve the Boundary Value Problems

Avatar-Based Natural Neural Network as a Dynamic Virtual Model

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