IL-6 signaling plays an important role in inflammatory processes in the body. While a number of models for IL-6 signaling are available, the parameters associated with these models vary from case to case as they are non-trivial to determine. In this...
A new parameter estimation method for a UAV braking system with unknown friction parameters is suggested. The unknown part containing friction is separated from the coupling system. The law of parameter updating is driven by the estimation error extr...
Parameter estimation for solar photovoltaic panels is a popular research topic in green energy. Model parameters can be used for fault diagnosis in solar panels. Artificial neural network (ANN) approaches have been developed to estimate the model par...
In recent years, the penetration of fuel cells in distribution systems is significantly increased worldwide. The fuel cell is considered an electrochemical energy conversion component. It has the ability to convert chemical to electrical energies as...
The parameters of electric machines play a substantial role in the control system which, in turn, has a great impact on machine performance. In this paper, a proposed optimal estimation method for the electrical parameters of induction motors is pres...
The uncertainty in parameter estimation arises from structural systems’ input and output measured errors and from structural model errors. An experimental verification of the shuffled complex evolution metropolis algorithm (SCEM-UA) for identif...
Parameters associated with electrical equivalent models of the photovoltaic (PV) system play a significant role in the performance enhancement of the PV system. However, the accurate estimation of these parameters signifies a challenging task due to...
Optimal tracking control aims to steer a dynamical system along a desired reference trajectory while minimizing a prescribed performance cost. This problem becomes substantially more difficult when both the controlled system dynamics and the target d...
Activated sludge models (ASMs) are often used in the simulation of the wastewater treatment process to evaluate whether the effluent quality parameters of a wastewater treatment plant meet the standards. The premise of successful simulation is to cho...
In this study, two different parameter estimation algorithms are studied and compared. Iterated EKF and a nonlinear optimization algorithm based on on-line search methods are implemented to estimate parameters of a given permanent magnet synchronous...
This paper presents a method for selecting the sampling time for induction machine parameter estimation from the machine line start measurements. the metaheuristic optimization method is used to find the optimal Prony exponential series approxiamtion...
Accurate parameter estimation is essential for modeling the statistical characteristics of ocean clutter. Common parameter estimation methods in generalized Pareto distribution models have limitations, such as restricted parameter ranges, lack of clo...
Accurate parameter estimation of solar cells is vital to assess and predict the performance of photovoltaic energy systems. For the estimation model to accurately track the experimentally measured current-voltage (I-V) data, the parameter estimation...
Parameter estimation plays an important role in improving the accuracy, control, and diagnostic performance of mechanisms, particularly in parallel mechanisms such as the Stewart platform, which are increasingly used in high-precision automation, adv...
This paper presents a two-stage optimization of the parameters of a seven-parameter equivalent circuit of three-phase induction motor. The initial parameters of this equivalent circuit are estimated by a method called the Engineering Method using the...
The utilization of solar photovoltaics (PV) in electricity generation is progressively increasing due to its environmental benefits, such as reducing power transmission costs and mitigating global warming. This research aims to enhance the effectiven...
In this paper, a modified version of a recent optimization algorithm called gradient-based optimizer (GBO) is proposed with the aim of improving its performance. Both the original gradient-based optimizer and the modified version, MGBO, are utilized...
Motion parameter estimation of a ground moving target is an important issue in synthetic aperture radar ground moving target indication (SAR-GMTI) which has significant applications for civilian and military. The SAR image of a moving target may be d...
Schottky barrier diodes (SBD) are crucial in the electronics sector. The electronic properties of SBD are characterized by three basic electrical parameters as the ideality factor (n), barrier height (ΦSB) and series resistance (RS). These parame...
Real-time estimation of transmission line (TL) parameters is essential for proper management of transmission and distribution networks. These parameters can be used to detect incipient faults within the line and hence avoid any potential consequences...
Multi-buoy sonar systems achieve target localization by receiving broadband Linear Frequency Modulation signals emitted from the transmitter. Accurate estimations of the parameters of Linear Frequency Modulation signals significantly enhance the loca...
Parameter estimation is an important part in the modeling of a hydro-turbine regulation system (HTRS), and the results determine the final accuracy of a model. A hydro-turbine is normally a non-minimum phase system with strong nonlinearity and time-v...
Background/Objectives: The effectiveness of chemotherapy in cancer treatment is often compromised by inter-patient variability, leading to suboptimal outcomes. Traditional dosing protocols rely on population-based models that do not account for indiv...
This paper deals with parameter estimation of single-phase transformer equivalent circuit by using Chaotic Optimization Approach (COA). Unknown transformer equivalent circuit parameters need to be accurately estimated for the best possible matching b...
Accurate parameter estimation of photovoltaic (PV) models is fundamentally a challenging nonlinear optimization problem, characterized by strong nonlinearity, high dimensionality, and multiple local optima. These characteristics significantly hinder...
In the developing landscape of photovoltaic (PV) technology, accuracy in simulating PV cell behaviour is dominant for enhancing energy conversion efficiency. This study introduces a new approach for parameter estimation in the three-diode PV model, a...
This paper addresses the critical challenge of optimizing the energy efficiency of induction motors, which are pivotal components across diverse industrial sectors due to their substantial energy consumption. Given the non-measurable internal paramet...
Photovoltaic (PV) panels are one of the popular green energy resources and PV panel parameter estimations are one of the popular research topics in PV panel technology. The PV panel parameters could be used for PV panel health monitoring and fault di...
Li-ion batteries possess significant advantages like large energy density, fast recharge, and high reliability; hence, they are widely adopted in electric vehicles, portable electronics, and military and aerospace applications. Albeit having their me...
Quantum gate estimation and tomography pipelines routinely combine intrinsically defined likelihoods with priors or regularization terms specified in local Euclidean coordinates. This practice implicitly replaces the Haar reference measure on
Recently, modelling and simulation have been used and applied to understand biological systems better. Therefore, the development of precise computational models of a biological system is essential. This model is a mathematical expression derived fro...
Constructing a reliable equivalent circuit of Li-Ion batteries using real operating conditions by estimating optimal parameters is mandatory for many engineering applications, as it controls the energy management of the battery in a hybrid system. Ho...
Magnetic Relaxometry (MRX) is a promising technique for probing the magnetic properties of nanoparticles with considerable potential in biomedical applications. It magnetizes magnetic nanoparticles through a direct current magnetic field to obtain me...
The parameter extraction of proton exchange membrane fuel cells (PEMFCs) has been an active area of study over the past few years, relying on metaheuristic optimizers and experimental datasets to achieve accurate current/voltage (I/V) curves. This wo...
Water quality models are of great importance for developing policies to control water pollution, with the model parameters playing a decisive role in the simulation results. It is necessary to introduce estimation through multi-objective parameters,...
Existing biodynamic models adopt apparent mass and seat-to-head transmissibility to predict the response of seated humans to whole-body vibration, limiting their ability to capture the actual response of distinct body segments in different excitation...
To achieve accurate control of Multi-Input and Multi-Output (MIMO) physical plants, it is crucial to obtain correct model expressions. In practice, the prevalence of both outliers and colored noise can cause serious interference with the industrial p...
We introduce a new method for estimating gravitational wave parameters. This approach uses a second-order likelihood optimization framework built into a machine learning system (JimGW). Current methods often rely on first-order approximations, which...
In order to enhance the stability of vehicle pose estimation within driving videos, a novel methodology for optimizing vehicle structural parameters is introduced. This approach hinges on evaluating the reliability of edge point sequences. Firstly, a...
With the increasing demand for electrical energy and the challenges related to its production, along with the need to be environmentally friendly to achieve sustainability for future generations, proton exchange membrane fuel cells (PEMFCs) are emerg...
Semi-empirical models remain among the most widely used tools for analyzing proton exchange membrane fuel cells (PEMFCs) because they provide a practical balance between physical interpretability and computational efficiency. Existing reviews primari...
Parameters of the solar cell equivalent circuit models have a significant role in assessing the solar cells’ performance and tracking operational variations. In this regard, estimating solar cell parameters is a difficult task because cells hav...
This study investigates Weibull distribution modeling for data under grouped observations. Two data grouping methods (equal-width and optimal) were compared for estimating parameters of the Weibull distribution using maximum likelihood estimation (ML...
Waveform design is a potentially significant approach to improve the performance of an imaging or detection system. Photoacoustic imaging is a rapidly developing field in recent years; however, photoacoustic waveform design has not been extensively i...
An optimal parameter estimation methodology of solid oxide fuel cell (SOFC) using modern optimization is proposed in this paper. An equilibrium optimizer (EO) has been used to identify the unidentified parameters of the SOFC equivalent circuit with t...
Simultaneous estimation of thermal properties can be challenging, especially when the parameters are temperature-dependent. Previous research has shown that by using a complementary experiment, temperature-dependent thermal conductivity can be estima...
In this work we present the model of a counter-current spray column in which a triglyceride (tripalmitic triglyceride) is hydrolyzed by water and leads to fatty acid (palmitic acid) and glycerol. A finite volume model (FVM) of the column was develope...
Proton Exchange Membrane Fuel Cells (PEMFCs) are crucial for the advancement of environmentally friendly hydrogen cars. It is one of the promising solutions for alternatives to conventional engines, primarily due to their ability to convert hydrogen...
Renewable energy sources such as solar are becoming increasingly popular worldwide. Mathematical derivation is used to show the structural framework of PV cells and their models with a single-diode configuration. This paper proposed a two-step optimi...
Recently, photovoltaic (PV) energy has been considered one of the most exciting new technologies in the energy sector. PV power plants receive considerable attention because of their wide applications. Consequently, it is important to study the param...
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