Search Results - (( parameter optimization method algorithm ) OR ( parameter estimation tool algorithm ))*
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Fitness-guided particle swarm optimization with adaptive Newton-Raphson for photovoltaic model parameter estimation
Published 2025Subjects:Article -
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Improving the Muskingum flood routing method using a hybrid of particle swarm optimization and bat algorithm
Published 2023“…Decision making; Disaster prevention; Floods; Routing algorithms; Water resources; Absolute deviations; Bat algorithms; Comparative analysis; Computational time; Flood routing; Muskingum models; Particle swarm optimization algorithm; Swarm algorithms; Particle swarm optimization (PSO); accuracy assessment; algorithm; comparative study; decision making; flood; flood forecasting; flood routing; numerical method; optimization; parameter estimation; water resource; United Kingdom; United States…”
Article -
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Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm
Published 2018“…Design of hydraulic structures, flood warning systems, evacuation measures, and traffic management require river flood routing. A common hydrologic method of flood routing is the Muskingum method. The present study attempted to develop a three-parameter Muskingum model considering lateral flow for flood routing, coupling with a new optimization algorithm namely, Improved Bat Algorithm (IBA). …”
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Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms
Published 2020“…Firstly, an improved EM (IEM) algorithm is presented to estimate the five parameters of the single PV-module system. …”
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Thesis -
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Robust Portfolio Mean-Variance Optimization for Capital Allocation in Stock Investment Using the Genetic Algorithm: A Systematic Literature Review
Published 2024journal::journal article -
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Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm
Published 2025“…The orthogonal learning mechanism improves the performance of the original GOOSE algorithm. This FC model uses the root mean squared error as the objective function for optimizing the unknown parameters. …”
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Predictive modelling of machining parameters of S45C mild steel
Published 2016“…The artificial neural network type Network Fitting Tool (NFTOOL) is used as a modeling technique for manipulating the ideal algorithm parameters. …”
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8
Optimization of operational policies for the Minab Reservoir, Southern Iran
Published 2012“…Rule curve for five possible scenarios were optimized by using Genetic Algorithms. The agricultural management optimization was applied to optimize the parameters like area, relative yield water requirements and irrigation efficiency. …”
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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing
Published 2024“…Firefly algorithm outperformed the other metaheuristic algorithms used to solve this proposed hybrid artificial intelligence model regarding parameter sensitivity. …”
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10
Combining Recursive Least Square and Principal Component Analysis for Assisted History Matching
Published 2014“…Even though RLS is a simple and effective method to estimate parameters, RLS have stability problem when number of parameters is high. …”
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Final Year Project -
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A memory-guided Jaya algorithm to solve multi-objective optimal power flow integrating renewable energy sources
Published 2025“…To ensure fair comparisons, parameter configurations for all algorithms are automated using the parameter tuning tool iterated racing (irace). …”
Review -
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Machine Learning Based Optimal Design of On-Road Charging Lane for Smart Cities Applications
Published 2025“…The algorithm not only aids in estimating the infrastructure cost of the charging lane but also predicts optimal design parameters using trained data. …”
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Development of a hybrid PSO-ANN model for estimating glucose and xylose yields for microwave-assisted pretreatment and the enzymatic hydrolysis of lignocellulosic biomass
Published 2018“…ANN is a powerful tool capable of determining the relationship between the desired input and output data while PSO was used as a robust population-based search algorithm to optimize the performance of the ANN model. …”
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Battery remaining useful life estimation based on particle swarm optimization-neural network
Published 2024“…This study contributes to the field by presenting the PSO NN as a highly effective tool for accurate battery RUL estimation, as evidenced by its superior performance over alternative methods.…”
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A Novel Hybrid Deep Learning Model Based on Simulated Annealing and Cuckoo Search Algorithms for Automatic Radiomics-Based COVID-19 Diagnosis
Published 2025“…To further enhance COVID-19 lesion estimation, novel optimization strategies, including a hybrid simulated annealing-cuckoo search (SA-CS) algorithm, are introduced alongside the original SA method. …”
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Power prediction using the wind turbine power curve and data-driven approaches / Ehsan Taslimi Renani
Published 2018“…To obtain the unknown vector of parameters of the MHTan, three heuristic optimization algorithms are employed to minimize the sum of squared residuals. …”
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Modeling of cupping suction system based on system identification method
Published 2022“…Cupping suction plant identification utilizing a nonlinear model based on the modified Sine Cosine Algorithm (mSCA). Moreover, there is a tool in MATLAB called System Identification Toolbox that can help to collect real measurement data samples. …”
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Undergraduates Project Papers -
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Prediction Of Petroleum Reservoir Properties Using Nonlinear Feature Selection And Ensembles Of Computational Intelligence Techniques
Published 2015“…The algorithms were implemented with optimized tuning parameters and validated with real-life porosity and permeability datasets obtained from diverse and heterogeneous petroleum reservoirs after they have passed on testing them with a benchmark dataset from the UCI Machine Learning Repository. …”
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Model-based hybrid variational level set method applied to object detection in grey scale images
Published 2024“…To tackle the persistent challenge of segmenting grayscale images with both uneven characteristics and high noise levels, a hybrid level-set algorithm based on kernel metrics is introduced. This algorithm leverages an improved multi-scale mean filter to mitigate grayscale inhomogeneity while reducing the impact of scale parameter selection. …”
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