Search Results - (( variable simulation modified algorithm ) OR ( parameter optimization _ algorithm ))
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1
Hybrid meta-heuristic algorithm for solving multi-objective aggregate production planning in fuzzy environment
Published 2017“…During the course of the present work, two fuzzy methods (modified Zimmermanns approach and modified angelovs approach ) and fourmeta-heuristics and hybrid meta heuristics including; simulated annealing (SA), modified simulated annealing (MSA), hybrid modified simulated annealing and simplex downhill (MSASD), hybrid modified simulated annealing and modified particle swarm optimization (MSAPSO) were proposed. …”
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2
Solving the integrated inventory supply chain problems using meta-heuristic methods / Seyed Mohsen Mousavi
Published 2018“…A Modified Particle Swarm Optimization (MPSO) algorithm, a Genetic Algorithm (GA), a modified fruit fly optimization algorithm (MFOA) and a simulated annealing (SA) algorithm were used to find the optimal solution. …”
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3
Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques
Published 2018“…To deal with these problems, this thesis introduces three approved intelligent controllers for hydropower generation. Firstly, a hybrid algorithm namely firefly particle swarm optimization (FPSO) and series division method (SDM) based on the practical swarm optimization and the firefly algorithm is proposed. …”
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4
Use of AR Block Processing for Estimating the State Variables of Power System
Published 2008“…Samples of the local utility network for 103-bus parameter are collected and simulated using Burg and Modified Covariance algorithm to estimate the state variables. …”
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5
Green retrofitting of building using BIM-based sustainability optimization
Published 2024“…This research aims to reform the existing building by modifying the design parameters for an inefficient building envelope based on BIM simulation and data optimization results to optimize the overall energy consumption. …”
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6
Green retrofitting of building using BIM-based sustainability optimization
Published 2024“…This research aims to reform the existing building by modifying the design parameters for an inefficient building envelope based on BIM simulation and data optimization results to optimize the overall energy consumption. …”
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7
Optimized clustering with modified K-means algorithm
Published 2021“…In order to obtain the optimum number of clusters and at the same time could deal with correlated variables in huge data, modified k-means algorithm was proposed. …”
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8
Information Theoretic-based Feature Selection for Machine Learning
Published 2018“…Three major factors that determine the performance of a machine learning are the choice of a representative set of features, choosing a suitable machine learning algorithm and the right selection of the training parameters for a specified machine learning algorithm. …”
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9
Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data
Published 2022“…The performance of the proposed method is illustrated using simulation study and on glass vessel data with 1920 variables, cardiomyopathy microarray data with 6319 variables, and octane data with 226 dimensions. …”
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10
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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11
An experimental study of neighbourhood based metaheuristic algorithms for test case generation satisfying the modified condition / decision coverage criterion
Published 2018“…Many researchers suggested the adoption of Modified Condition / Decision Coverage (MC/DC) criterion as a solution to the problem particularly when the inputs involve Boolean variables. …”
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Comparing three methods of handling multicollinearity using simulation approach
Published 2006“…The algorithm is described and for the purpose of comparing the three methods, simulated data sets where the number of cases was less than the number of observations were used. …”
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14
Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems
Published 2011“…The main idea is the integration of optimal control and parameter estimation. In this work, a simplified model-based optimal control model with adjustable parameters is constructed. …”
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15
Modifying maximum likelihood test for solving singularity and outlier problems in high dimensional cases
Published 2021“…The performance of MLѡвсн and four more modified ML-tests, namely MLtests with banded Cholesky estimator MLвсн with Thresholding MLтн with Weiszfeld Algorithm MLѡ and with Weiszfeld’s Algorithm Estimator and Thresholding MLѡтн had been examined using Type I error and power of test values in a simulation study. …”
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16
Enhanced segment particle swarm optimization for large-scale kinetic parameter estimation of escherichia coli network model
Published 2021“…In this regard, a Local Sensitivity Analysis, Segment Particle Swarm Optimization (Se-PSO) algorithm, and the Enhanced Segment Particle Swarm Optimization (ESe-PSO) algorithm was adapted and proposed to estimate the parameters. …”
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17
Finite impulse response optimizers for solving optimization problems
Published 2019“…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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18
Parameters optimization of surface grinding process with particles swarm optimization, gravitational search, and sine cosine algorithms: a comparative analysis
Published 2018“…In this paper, three optimization algorithms which are particle swarm optimization (PSO), gravitational search, and Sine Cosine algorithms are employed to optimize the grinding process parameters that may either reduce the cost, increase the productivity or obtain the finest surface finish and resulting a higher grinding process performance. …”
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19
A new metaphor-less algorithms for the photovoltaic cell parameter estimation
Published 2023“…Multiobjective optimization; Parameter estimation; Photoelectrochemical cells; Photovoltaic cells; Solar power generation; Cell parameter; Estimated parameter; Local minimums; Optimization algorithms; Pre-mature convergences; Solar cell parameters; Solar photovoltaic system; Solar PVs; Solar cells…”
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20
Finite impulse response optimizers for solving optimization problems
Published 2019“…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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