مشخصات مقاله | |
ترجمه عنوان مقاله | طراحی سیاست سرمایه گذاری مبتنی بر EID برای سیستم های مالی پرشی تصادفی فازی |
عنوان انگلیسی مقاله | EID-based sliding mode investment policy design for fuzzy stochastic jump financial systems |
انتشار | مقاله سال 2019 |
تعداد صفحات مقاله انگلیسی | 9 صفحه |
هزینه | دانلود مقاله انگلیسی رایگان میباشد. |
پایگاه داده | نشریه الزویر |
نوع نگارش مقاله |
مقاله پژوهشی (Research Article) |
مقاله بیس | این مقاله بیس نمیباشد |
نمایه (index) | Scopus – Master Journals List – JCR |
نوع مقاله | ISI |
فرمت مقاله انگلیسی | |
ایمپکت فاکتور(IF) |
5.953 در سال 2018 |
شاخص H_index | 46 در سال 2019 |
شاخص SJR | 2.019 در سال 2018 |
شناسه ISSN | 1751-570X |
شاخص Quartile (چارک) | Q1 در سال 2018 |
مدل مفهومی | ندارد |
پرسشنامه | ندارد |
متغیر | ندارد |
رفرنس | دارد |
رشته های مرتبط | مدیریت، اقتصاد |
گرایش های مرتبط | مدیریت مالی، اقتصاد مالی |
نوع ارائه مقاله |
ژورنال |
مجله / کنفرانس | تحلیل غیر خطی: سیستم های هیبریدی – Nonlinear Analysis: Hybrid Systems |
دانشگاه | Department of Mathematics – Bharathiar University – India |
کلمات کلیدی | سیستم مالی تصادفی غیر خطی، برآوردگر EID، مدل فازی Takagi-Sugeno، طراحی سیاست سرمایه گذاری حالت Sliding |
کلمات کلیدی انگلیسی | Nonlinear stochastic financial system, EID estimator, Takagi–Sugeno fuzzy model, Sliding mode investment policy design |
شناسه دیجیتال – doi |
https://doi.org/10.1016/j.nahs.2018.08.004 |
کد محصول | E10261 |
وضعیت ترجمه مقاله | ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید. |
دانلود رایگان مقاله | دانلود رایگان مقاله انگلیسی |
سفارش ترجمه این مقاله | سفارش ترجمه این مقاله |
فهرست مطالب مقاله: |
Abstract Keywords 1 Introduction 2 Problem formulation and preliminaries 3 Main results 4 Numerical simulations 5 Conclusion Appendix. References |
بخشی از متن مقاله: |
abstract
This paper proposes a sliding mode investment policy design for nonlinear stochastic financial systems which can be represented by the well-known Takagi–Sugeno fuzzy model. When modeling the financial systems, it is more important to consider the unpredictable investment changes and worldwide unpredictable events which can be regarded as external disturbances. The equivalent-input-disturbance (EID) approach combined with sliding mode investment policy design is implemented to reject the unpredictable investment changes for having better investment. Moreover, the Luenberger state observer is constructed for the addressed financial system to estimate the unpredictable investment changes and worldwide unpredictable events. More precisely, a sliding mode investment policy design is developed by solving the obtained linear matrix inequality (LMI)-based constrained algorithm. Finally, the obtained results of the addressed fuzzy stochastic financial system are verified through numerical simulation to show efficiency of the proposed sliding mode investment policy design. Introduction In our day-to-day life, financial market is more important in which individuals exchange money related securities and commodities at low exchanges costs [1,2]. In order to stabilize the real economy of the companies, investors and governments, it is much essential to analyze the dynamical behavior between the financial market and the real economy. In general, the main objective of the companies, investors and governments are to increase the profit and reduce the risk. Recently, significant attention has been paid by the research communities on studies of financial systems due to complex process of business operations. In general, financial systems are influenced by a several economic factors, such as national and international situation changes, the variable interest rate, wrong economy policy, oil price change and unpredictable investment-environmental changes [3]. Moreover, in practice, many economic factors are not always be deterministic due to unpredictable sudden investments, wars and natural disorder. Therefore, in the dynamics of financial control systems these kind of unknown disturbance factors should be taken into consideration. On the other hand, the disturbance rejections in dynamical control systems can be handled by various design methodologies [4–9]. In particular, the sliding mode control (SMC) is one of the most recognized controller to reject the effects of matched disturbances and the modeling error in the dynamical control system [10–15]. Generally, sliding mode control contains two steps; one is to design the sliding surface in which the system has desired properties such as stability, disturbance rejection capability and tracking ability and the next is to design the discontinuous controller such that the system state reach the sliding surface in the finite time [16–19]. |