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سخنرانان کلیدی سمینار

1- پرفسور چانگ پین لی  از دانشگاه شانگهای چین

عنوان سخنرانی

  "Stability and logarithmic decay of solution to Hadamard-type fractional differential system"

:Abstract
The so-called logarithmic decay indicates that the solution to the evolutionary equation has algebraic asymptotic decay in the sense of logarithmic function. It is often used to characterize the ultra slow process, such as creep in igneous rocks. In this talk, we mainly introduce the stability and logarithmic decay of solution to the Hadamard-type fractional differential system including the linear and nonlinear cases.
 
2- دکتر حبیب ایزدخواه از دانشگاه تبریز

عنوان سخنرانی 

                                                           "Deep Learning: Applications, Theory, and Challenges"

:Abstract
Artificial Intelligence, Machine Learning, and Deep Learning have become the latest hot buzzwords. Deep learning being one of the hottest areas of contemporary research. Deep learning, as an emerging branch from machine learning, is a good solution for big data analytics. Deep learning methods have been extensively applied to various fields of science and engineering, including computer vision, differential equations, speech recognition, natural language processing, social network analyzing, and bioinformatics, where they have produced results comparable to and in some cases superior to domain experts. In this talk, several applications of deep learning in science and technology, the main architectures of deep learning and the challenges faced by models based on deep learning will be discussed.
 
3-پرفسور یوبین یان از دانشگاه چستر انگلستان

عنوان سخنرانی 

                                             "Continuous Galerkin cG(1) method for solving subdiffusion problem "

:Abstract
A continuous Galerkin time stepping method cG(1)  is introduced and analyzed for subdiffusion problem in an abstract setting. The approximate solution will be sought as a continuous piecewise linear function in time $t$ and the test space is based on the discontinuous piecewise constant functions. We prove that the proposed time stepping method has the convergence order $O( au^{2}), , alpha in (0, 1)$ for general sectorial elliptic operators for nonsmooth data by using the Laplace transform method, where $ au$ is the time step size. This convergence order is higher than the convergence orders of the popular convolution quadrature methods (e.g., Lubich's convolution methods) and L-type methods (e.g., L1 method), which have only $O( au)$ convergence for the nonsmooth data. Numerical examples are given to verify the robustness of the time discretization schemes with respect to data regularity.
 
4-دکتر غلامرضا رکنی از دانشگاه تهران
عنوان سخنرانی  
                                                         "Control Theory and Dynamical Systems"
Abstract: 
A dynamical system is a mathematical system with specific objects and axioms. On the other hand, a control system is a mathematical system with particular objects and axioms similar to the objects and axioms of dynamical systems. Regarding these similarities, a control system has more objects than a dynamical system with slightly different axioms. Along with these similarities and differences, two lines of relations between these two mathematical systems will be discussed. The first is the roles and applications of the results of dynamical systems in control theory. The second is the method of putting a control system into the framework of the dynamical system.
 
5-دکتر آرمان دبیری از دانشگاه ایلینویز آمریکا
 
 
عنوان سخنرانی  
                                 "Nonlocal Operators in Dynamics and Control: Theories and Applications"
Abstract:
In this talk, a new stability criterion, called fractional Chebyshev collocation (FCC), is presented to study the stability of linear dynamical systems with nonlocal operators such as delays, fractional operators, and periodic coefficients. The FCC stability criterion can be applied to broad classes of linear dynamical systems compared to the current stability criteria that are particularly limited to a few classes of linear dynamical systems. It can examine the stability of linear dynamical systems with several nonlocal operators. As a result of this fundamental study, some open problems in this field were solved. In addition, the FCC framework is developed for obtaining a better control performance for linear dynamical systems with a large degree of freedom. The FCC framework can be applied to various applications such as flexible robots, consensus control, and autonomous vehicles.framework can be applied to various applications such as flexible robots, consensus control, and autonomous vehicles.
6-دکتر علی فروش باستانی از مرکز تحصیلات تکمیلی زنجان
 
عنوان سخنرانی  
                                 "Investigating the Performance of Portfolio Insurance Strategies under a Regime Switching Markov Model "
Abstract:
Portfolio insurance (PI) strategies are structural methods that provide a certain level of certainty by setting a floor value. In other words, using these strategies, one can achieve a predetermined minimum return. PI strategies, while maintaining the potential for capital growth in bull markets, provide downside protection in the bear market and at the end of the investment horizon, provide a guaranteed minimum return. This study explains how to construct a portfolio and allocate assets by using these strategies and examines the performance of a constant proportion portfolio insurance (CPPI) strategy and value at risk based portfolio insurance (VBPI). In order to evaluate the performance of constant proportion portfolio insurance strategy and value at risk based portfolio insurance, first the mathematical model of the Constrained Constant Proportion portfolio insurance is presented. In the Constrained case risk-free borrowing is not possible which makes the model more realistic. By using the Fourier transform of the characteristic function, the density function of returns has been extracted. By using the Density Function, the value at risk is calculated at the desired confidence levels, and finally, the mathematical model of the risk-based approach is presented. A variable-rate model is used to estimate the risk-taking movement of the asset, which is closer to reality. To estimate the dynamics of the risky asset, a regime-switching model has been used to make the model closer to reality. The results show that both strategies have been successful in controlling risk and this performance improves with increasing confidence level and frequency of portfolio rebalancing. Omega measure shows that the performance of the constant proportion portfolio insurance is better at low thresholds. In addition, the dispersion of the simulated results for the final value of the portfolios showed that the constant proportion portfolio insurance works better in protecting the floor. Portfolio insurance strategies can dramatically improve the controlling of downside risk relative to buy and hold strategy and the performance of CPPI strategy is better than VBPI according to the performance measures.
 
 
 

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