This study investigates optimal control problems described by fractional differential equations, with the control vector components subject to algebraic constraints. Two case studies are analyzed: an illustrative exam...
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ISBN:
(数字)9798331515799
ISBN:
(纸本)9798331515805
This study investigates optimal control problems described by fractional differential equations, with the control vector components subject to algebraic constraints. Two case studies are analyzed: an illustrative example designed to test the algorithm’s effectiveness and a biologically significant model of acute myeloid leukemia (AML), which applies optimal control theory to design therapeutic strategies under medical constraints. The methodology transforms fractional differential equations into equivalent ordinary differential equations using the framework of Atanacković and Stanković. L.S. Pontryagin’s maximum principle is then applied to derive control functions that satisfy the algebraic constraints, followed by numerical optimization of the Hamiltonian function. We formally parsed the problem of dynamic optimization into a static optimization problem using the Forward-Backward Sweep Method (FBSM). The approach is validated through comprehensive numerical simulations, demonstrating its robustness and applicability to real-world problems.
This paper evaluates two common methods for trajectory estimation: the Extended Kalman Filter (EKF), the Unscented Kalman Filter (UKF). The EKF and UKF are well-established recursive filtering techniques commonly used...
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ISBN:
(数字)9798331515799
ISBN:
(纸本)9798331515805
This paper evaluates two common methods for trajectory estimation: the Extended Kalman Filter (EKF), the Unscented Kalman Filter (UKF). The EKF and UKF are well-established recursive filtering techniques commonly used for nonlinear state *** performance of these methods is compared through their implementation on a standard trajectory estimation problem, with a focus on assessing their accuracy.
This paper investigates reinforcement learning (RL) as a practical framework for achieving optimal adaptive control across several simple dynamical system models. All experiments were conducted using the Proximal Poli...
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This study investigates optimal control problems described by fractional differential equations, with the control vector components subject to algebraic constraints. Two case studies are analyzed: an illustrative exam...
详细信息
This paper evaluates two common methods for trajectory estimation: the Extended Kalman Filter (EKF), the Unscented Kalman Filter (UKF). The EKF and UKF are well-established recursive filtering techniques commonly used...
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Brain networks typically exhibit characteristic synchronization patterns where several synchronized clusters coexist. On the other hand, neurological disorders are considered to be related to pathological synchronizat...
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The novel Coronavirus disease 2019(COVID-19)pandemic has begun in China and is still affecting thousands of patient livesworldwide *** X-ray and Computed Tomography are the gold standardmedical imaging modalities for ...
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The novel Coronavirus disease 2019(COVID-19)pandemic has begun in China and is still affecting thousands of patient livesworldwide *** X-ray and Computed Tomography are the gold standardmedical imaging modalities for diagnosing potentially infected COVID-19 cases,applying Ultrasound(US)imaging technique to accomplish this crucial diagnosing task has attracted many physicians *** this article,we propose two modified deep learning classifiers to identify COVID-19 and pneumonia diseases in US images,based on generative adversarial neural networks(GANs).The proposed image classifiers are a semi-supervised GAN and a modifiedGANwith auxiliary *** one includes a modified discriminator to identify the class of the US image using semi-supervised learning technique,keeping its main function of defining the“realness”of tested *** tests have been successfully conducted on public dataset of US images acquired with a convex US *** study demonstrated the feasibility of using chest US images with two GAN classifiers as a new radiological tool for clinical check of COVID-19 *** results of our proposed GAN models showed that high accuracy values above 91.0%were obtained under different sizes of limited training data,outperforming other deep learning-based methods,such as transfer learning models in the recent ***,the clinical implementation of our computer-aided diagnosis of US-COVID-19 is the future work of this study.
The rapid development of digital technology has brought about the challenge of ensuring information security. Cryptography and steganography are among the various techniques available to address this challenge. These ...
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Departure Time Planner (DTP) helps to efficiently manage the commute plan by providing smart travel assistance which suggests a departure from a given origin to a destination, given the desired arrival time at the des...
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Renewable energy had drawn a lot of attention for researchers, technocrats and industry for sustainable development of nation and also drawn vide attention globally. Specially solar energy has been getting attention s...
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