Today's smart engineering systems are often faced with situations that are structurally uncertain, informationally incomplete, and non-probabilistically ambiguous, especially for electrical systems. ARDL models are limited in applications in complex computational environments where the uncertainty is due to vagueness, not randomness, and assume the exact parametric representation of the models and the structure of the stochastic uncertainty. This study proposes a new soft-computing paradigm using Fuzzy Autoregressive Distributed Lag (FARDL) models and compares the performance of the Linear Programming (LP) and Quadratic Programming (QP) estimation algorithms using large-scale parallel Monte Carlo simulations to overcome these drawbacks as well as fuzzy differential equations, especialy for electrical circuits and machines. In contrast to the previous works that mainly adopted the symmetric triangular fuzzy coefficients without any theoretical considerations, the proposed framework provides a mathematical foundation for fuzzy membership selection and examines the robustness of the estimators under symmetric triangular, asymmetric triangular, and trapezoidal fuzzy topologies. To evaluate the performance of the system, a Monte Carlo simulation framework is implemented under six sample sizes (T = 10, 15, 20, 30, 50, 100) and under different levels of structural complexity. The simulation results show that the QP method is always superior to the LP paradigm in terms of the estimation error of the center trajectory and the spread of uncertainty of the parameters in terms of Fuzzy Degree (FD). This is especially true in small sample situations, where the operational advantage is more pronounced, making it particularly useful for systemic modeling in data-sparse situations. Moreover, the proposed framework-based fuzzy differential equation offers a mathematically efficient tool to model mysterious engineering systems like network-based smart grids, control models, communication systems, and cyber-based frameworks. The combination of fuzzy dynamic approaches allows a reliable scheme and uncertainty quantification-based system for complex engineering environmental conditions, whereas deterministic schemes are becoming inadequate.
Skull image separation is one of the initial procedures used to detect brain abnormalities. In an MRI image of the brain, this process involves distinguishing the tissue that makes up the brain from the tissue that does not make up the brain. Even for experienced radiologists, separating the brain from the skull is a difficult task, and the accuracy of the results can vary quite a little from one individual to the next. Therefore, skull stripping in brain magnetic resonance volume has become increasingly popular due to the requirement for a dependable, accurate, and thorough method for processing brain datasets. Furthermore, skull stripping must be performed accurately for neuroimaging diagnostic systems since neither no
... Show MoreThis article aims to explore the importance of estimating the a semiparametric regression function ,where we suggest a new estimator beside the other combined estimators and then we make a comparison among them by using simulation technique . Through the simulation results we find that the suggest estimator is the best with the first and second models ,wherealse for the third model we find Burman and Chaudhuri (B&C) is best.
In this paper, a novel flow control strategy which is the inlet throttled pump was used to design an angular velocity control system for rotary actuator. Inlet throttled systems have good performance in addition to their high efficiency compared to traditional valve controlled systems. The flow in the proposed system is adjusted by a valve that is positioned at the pump inlet with the purpose of reducing the energy loses across the valve. This regulated flow is used then to control the actuator angular velocity. The system was modeled and the open loop stability and performance were studied. In order to improve the system performance, Robust-Proportional-Integral-Derivative (RPID) and structured singular value (M@#@) controllers have been d
... Show MorePID (proportional-integral-derivative) and Mu controllers are widely used in electro-hydraulic servo systems due to their effectiveness and ease of implementation. This paper explores using particle swarm optimization (PSO) for tuning traditional and robust PID controllers, along with D-K iteration for Mu controller tuning. Three controller types: conventional PID (CPID), robust PID (RPID), and structured singular value controllers are developed, while analyzing multiplicative uncertainty with six uncertain coefficients. Their findings indicated that both PID (CPID and RPID) and Mu controllers maintained system stability. Notably, the Mu controller can handle coefficient uncertainty without a pure integral term, while the RPID controller de
... Show MoreComputer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes
... Show MoreThis paper explores a fuzzy-logic based speed controller of an interior permanent magnet synchronous motor (IPMSM) drive based on vector control. PI controllers were mostly used in a speed control loop based field oriented control of an IPMSM. The fundamentals of fuzzy logic algorithms as related to drive control applications are illustrated. A complete comparison between two tuning algorithms of the classical PI controller and the fuzzy PI controller is explained. A simplified fuzzy logic controller (FLC) for the IPMSM drive has been found to maintain high performance standards with a much simpler and less computation implementation. The Matlab simulink results have been given for different mechanical operating conditions. The simulated
... Show MoreDespite their potential as a sustainable energy technology, the operation of proton exchange membrane fuel cells (PEMFCs) in sub-freezing conditions remains a critical challenge due to the risk of ice formation and performance degradation. This study introduces a new passive thermal management technique using strategically arranged multi-layer phase change materials (PCMs) to address this challenge. A numerical model was developed to evaluate the thermal behavior across various PCM configurations, incorporating one, two, and three layers arranged both in parallel and series with distinct melting points ranging from 55 to 65 ◦C. The results show that multi-layer PCM configurations provide significant improvements over the single-layer base
... Show MoreAbstract The study aimed at reviewing translation theories proposed to address problems in translation studies. To the end, translation theories and their applications were reviewed in different studies with a focus on issues such as critical discourse analysis, cultural specific items and collocation translation.