Search Results - (( time optimization mead algorithm ) OR ( parameter estimation based algorithm ))
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1
A Novel Polytope Algorithm based on Nelder-mead method for localization in wireless sensor network
Published 2024“…This work proposes a novel and rigorous efficiency localization algorithm utilizing a simplex optimization approach for node localization. …”
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2
Fitting time-varying coefficients SEIRD model to Covid-19 cases in Malaysia
Published 2023“…Nelder-Mead outperforms the other optimization algorithm with the least error. …”
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3
Evaluation of energy-saving potential for optimal time response of HVAC control system in smart buildings
Published 2023“…Controllers; Delay control systems; Energy efficiency; Gradient methods; Intelligent buildings; Membership functions; Optimal systems; Optimization; Response time (computer systems); Semiconductor device manufacture; Thermal comfort; Water craft; Cluster adaptive training; Energy efficient building; Energy saving potential; Fuzzy membership function; Manufacturing industries; Nelder-Mead simplex search; Semiconductor manufacturing process; Temperature and humidities; HVAC; algorithm; building; control system; electronic equipment; energy conservation; manufacturing; residential energy; temporal analysis…”
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4
Optimizing the SEIRD model for COVID-19 in Malaysia using pymoo framework
Published 2025“…To solve this, the Nelder-Mead and Pattern Search algorithms were recommended. …”
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5
Optimized PID controller of DC-DC buck converter based on archimedes optimization algorithm
Published 2023“…Leveraging the metaheuristic algorithm, the PID controller is optimized to minimize voltage errors, reduce overshoot, and enhance response time. …”
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6
Single and Multiple variables control using Tree Physiology Optimization
Published 2017“…In the proposed method, each shoot from each branch search for possible solution in parallel and the fitness is evaluated based on all best values found by branch search. The proposed algorithm is also compared with deterministic gradient-free algorithm: Nelder-Mead simplex (NMS) and another metaheuristic algorithm: Particle Swarm Optimization (PSO). …”
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7
Semiparametric inference procedure for the accelarated failure time model with interval-censored data
Published 2019“…A computationally simple two-step iterative algorithm, called estimationapproximation algorithm, is introduced for estimating the parameters of the model on the basis of the rank estimators. …”
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8
Finite impulse response optimizers for solving optimization problems
Published 2019“…In this work, three new estimation-based metaheuristic algorithms are introduced. …”
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9
An improved scatter search algorithm for parameter estimation in large-scale kinetic models of biochemical systems
Published 2019“…Methods: This paper proposes an improved scatter search algorithm to address the challenging parameter estimation problem. …”
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10
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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11
An Improved Scatter Search Algorithm for Parameter Estimation in Large-Scale Kinetic Models of Biochemical Systems
Published 2019“…Methods: This paper proposes an improved scatter search algorithm to address the challenging parameter estimation problem. …”
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12
Finite impulse response optimizers for solving optimization problems
Published 2019“…In this work, three new estimation-based metaheuristic algorithms are introduced. …”
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13
An enhanced segment particle swarm optimization algorithm for kinetic parameters estimation of the main metabolic model of Escherichia coli
Published 2020“…In this study, an Enhanced Segment Particle Swarm Optimization algorithm (ESe-PSO) was proposed for kinetic parameters estimation. …”
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14
Simultaneous Computation of Model Order and Parameter Estimation for System Identification Based on Gravitational Search Algorithm
Published 2015“…In this paper, a technique termed as Simultaneous Model Order and Parameter Estimation (SMOPE), which is specifically based on Gravitational Search Algorithm (GSA) is proposed to combine model order selection and parameter estimation in one process. …”
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15
Enhanced segment particle swarm optimization for large-scale kinetic parameter estimation of escherichia coli network model
Published 2021“…However, the large-scale kinetic parameters estimation using optimization algorithms is still not applied to the main metabolic pathway of the E. coli model, and they’re a lack of accuracy result been reported for current parameters estimation using this approach. …”
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16
Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach
Published 2022“…The most popular method to solve parameter estimation problem is using optimization algorithm that easily trap to local minima and poor in exploitation to find the good solutions. …”
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17
Parameter estimation of cocomo model using the jaya algorithm for software cost estimation
Published 2019“…This thesis proposed the Jaya algorithm based on estimation of the software based on the COCOMO I model. …”
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18
Estimation Of Weibull Parameters Using Simulated Annealing As Applied In Financial Data
Published 2023“…The performance of the SA algorithm has been explored in terms of accuracies and estimation errors. …”
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19
An Improved Hybrid of Particle Swarm Optimization and the Gravitational Search Algorithm to Produce a Kinetic Parameter Estimation of Aspartate Biochemical Pathways
Published 2017“…The results show that the proposed algorithm outperformed other standard optimization algorithms in terms of accuracy and near-optimal kinetic parameter estimation. …”
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Simultaneous computation of model order and parameter estimation for ARX model based on single swarm and multi swarm simulated Kalman filter
Published 2017“…Simultaneous Model Order and Parameter Estimation (SMOPE) and Simultaneous Model Order and Parameter Estimation based on Multi Swarm (SMOPE-MS) are two techniques of implementing meta-heuristic algorithm to iteratively establish an optimal model order and parameters simultaneously for an unknown system. …”
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