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Estimation of photovoltaic models using an enhanced Henry gas solubility optimization algorithm with first-order adaptive damping Berndt-Hall-Hall-Hausman method
Published 2024“…Then in terms of methodology, the Enhanced Henry Gas Solubility Optimization (EHGSO) algorithm is combined with the Sine-Cosine mutualism phase of Symbiotic Organisms Search (SOS) for efficiently estimating the unknown parameters of PV models. …”
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Parameter estimation in computational systems biology models: a comparative study of initialization methods in global optimization
Published 2022“…In addition, the different initialization methods also influenced model accuracy. …”
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Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…These algorithms are inspired by the estimation capability of the well-known Kalman filter estimation method. …”
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Optimization of multipurpose reservoir operation using evolutionary algorithms / Mohammed Heydari
Published 2017“…An improved particle swarm algorithm (HPSOGA) is used to solve complex problems of water resources optimization. …”
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LEMABE: a novel framework to Improve analogy-based software cost estimation using learnable evolution model
Published 2021“…Then, MMRE, PRED (0.25), and MdMRE criteria have been used to evaluate and compare the proposed method against other evolutionary algorithms. Employing the proposed method showed considerable improvement in estimating software cost estimation.…”
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Modeling and Prediction of The Mechanical Properties of Feedstock by Cooling-Slope Casting Process using MOJaya Algorithm
Published 2024“…Hence, computational methods namely the MOJaya algorithm are utilized to model and optimize the parameters of CS to address the CS problem and forecast the performance of the feedstock. …”
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Modeling and Prediction of the mechanical properties of feedstock by cooling-slope casting process using MOJaya algorithm
Published 2024“…Hence, computational methods namely the MOJaya algorithm are utilized to model and optimize the parameters of CS to address the CS problem and forecast the performance of the feedstock. …”
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A hybrid simple exponential smoothing-barnacles mating optimization approach for parameter estimation: Enhancing COVID-19 forecasting in Malaysia
Published 2025“…Therefore, this study aims to propose a new hybrid model, the Single Exponential Smoothing (SES)-Barnacles Mating Optimization (BMO) algorithm, to estimate the optimal smoothing parameter alpha and initial value that can improve the percentage of forecast accuracy. …”
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Using genetic algorithms to optimise land use suitability
Published 2012“…The Erosion Potential Method (EPM) used in erosion estimation and sediment yield of the study. …”
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Improved genetic algorithm for direct current motor high speed controller implemented on field programmable gate array
Published 2019“…The third methodology is to integrate the proposed controller on FPGA, using a new method to run the design based simulink model. …”
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Integration of knowledge-based seismic inversion and sedimentological investigations for heterogeneous reservoir
Published 2020“…The extracted rules and optimized number rules then would be used for rule-based porosity estimation. …”
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Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources
Published 2021“…The proposed DNN algorithm is structured to incorporate initial/boundary conditions in cylindrical coordinates and approximate the solution without the aid of any simulated or training data. …”
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Modeling and control of a Pico-satellite attitude using Fuzzy Logic Controller
Published 2010“…In this regards, a new method of Pico-satellite attitude control using Mamdani Fuzzy Logic Principles is introduced. …”
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JOINT TORQUEESTIMATION OF sEMG SIGNALS BASED ON INTELLIGENT TECHNIQUES FOR ROBOTIC ASSISTIVE SYSTEM
Published 2014“…Thereafter, the actual joint torque was acquired through dynamic modeling. Finally, simulation was conducted on nine mathematical models to convert the sEMG signals to estimated joint torque using optimization techniques such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO).…”
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Optimization of Microbial Electrolysis Cell for Sago Mill Wastewater Derived Biohydrogen via Modeling and Artificial Neural Network
Published 2023“…The model reliability describes the second sub-objective, which is to determine the feasible operating window of the MEC using multiple-objective optimization based on the nonlinear convex method using gradient descent algorithm as the objective function in maximizing the percentage efficiency of the MEC after validating the mathematical model. …”
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Intelligent image noise types recognition and denoising system using deep learning / Khaw Hui Ying
Published 2019“…Unlike traditional methods that usually start with detection and followed by denoising, the model initially leverages the powerful ability of deep CNN architecture to separate noise from noisy image, then adopts PSO to pinpoint the most optimized threshold values for detecting impulse noisy pixels. …”
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Robust techniques for linear regression with multicollinearity and outliers
Published 2016“…The ordinary least squares (OLS) method is the most commonly used method in multiple linear regression model due to its optimal properties and ease of computation. …”
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Performance Modeling And Size Optimization Of A Standalone Photovoltaic System
Published 2013“…Furthermore, SAPV components sizing method was formulated with a nonlinear unconstrained optimization technique by using first derivative method. …”
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A comprehensive analysis of surface electromyography for control of lower limb exoskeleton
Published 2016“…Obviously, selecting four muscles to attain a full joint moment and motion is not sufficient, therefore we introduced the net joint moment obtained from the inverse dynamics to optimize the predicted joint moment. Initial estimate of the model is obtained from literature review while the Levenderg-Marquardt (LM) method is applied to solve the nonlinear least squares optimization problem. …”
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