Search Results - (( rate estimation methods algorithm ) OR ( simulation optimization based algorithm ))
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1
Development of optimization Alghorithm for uncertain non-linear dynamical system
Published 2004“…Based on the results of these simulations, we compared the number of iterations needed by each algorithm to arrive at the optimal solution and the CPU time taken for each algorithm to execute the search. …”
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Monograph -
2
Application of Evolutionary Algorithm for Assisted History Matching
Published 2014“…While the automatic method focus on optimization which is normally computer based. …”
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Final Year Project -
3
Analysis of multiexponential transient signals using interpolation-based deconvolution and parametric modeling techniques
Published 2003“…Direct deconvolution approach often leads to poor resolution of ihe estimated decay rates since the fast Fourier transform (FFT) algorithm is used to analyze the resulting deconvolved data. …”
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Proceeding Paper -
4
On iterative low-complexity algorithm for optimal antenna selection and joint transmit power allocation under impact pilot contamination in downlink 5g massive MIMO systems
Published 2020“…From Fig.4.3, in chapter 4, the maximal value of data rates = (17.4, 16.9,16.3) bits/s/Hz, when the optimal transmit pilot reuse was = (14, 17, 20), with accounting channel estimation, when the number of antennas was . …”
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Thesis -
5
Integration of Computer Simulation, Design of Experiments and Particle Swarm Optimization to Optimize the Production Line Efficiency
Published 2016“…The goal of this paper is to optimize the productivity of manufacturing system by integrating computer simulation, design of experiments (DOE) and particle swarm optimization (PSO) algorithm. …”
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Article -
6
Parameter estimation of multicomponent transient signals using deconvolution and ARMA modelling techniques
Published 2003“…An improved method that is based of the combination of Gardner transformation, optimal compensation deconvolution, and signal modelling techniques is suggested in this paper. …”
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Article -
7
Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources
Published 2021“…The simulated results and analysis demonstrate an excellent agreement between the proposed algorithm and non-Newtonian fluids flow attributes. …”
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Article -
8
Robust estimation methods for fixed effect panel data model having block-concentrated outliers
Published 2019“…The Ordinary Least Squares (OLS) is the commonly used method to estimate the parameters of fixed effect panel data model. …”
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Thesis -
9
Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS
Published 2017“…Since extreme learning machine is a non-iterative estimation procedure, it is faster than gradient-based algorithms which are iterative. …”
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10
Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh
Published 2015“…The simulation results show the effectiveness of the ARDE method over other conventional techniques, transcending the limits of the existing state-of-the-art algorithms in estimating the parameters of robot. …”
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Thesis -
11
Product optimization of a fed-batch fermentation process
Published 2007“…From this two optimization approaches, it is possible to estimate the optimal operating conditions as substrate feed rate so that the systems presents high performance within threshold value limit. …”
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Conference or Workshop Item -
12
Adapting perturbation voltage for variable speed micro-hydro using particle swarm optimization (PSO)
Published 2022“…MicroHydro that operates in variable speed mode are sensitive to the changes of flow rate and proved to have wide operating point. The Perturb and Observe (P&O) based maximum power point tracking (MPPT) was applied to the VS-MH and based on simulation. …”
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Proceedings -
13
Comparison And Assessment Of Methods Used To Estimate Egfr In Ckd Patients: The Role Of Clinical Pharmacist And Direct Medical Costs
Published 2021“…This study aimed to evaluate GFR estimating algorithms for medication dosing in CKD patients. …”
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Thesis -
14
Optimization-based simulation algorithm for predictive-reactive job-shop scheduling of reconfigurable manufacturing systems
Published 2022“…In this case, the effectiveness and reliability of RMS is increase by combining the simulation with the optimization algorithm.…”
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Thesis -
15
Simulated Kalman Filter: A Novel Estimation-based Metaheuristic Optimization Algorithm
Published 2016“…In this paper, a new population-based metaheuristic optimization algorithm, named Simulated Kalman Filter (SKF) is introduced. …”
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Conference or Workshop Item -
16
Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…In this research, two novel estimation-based metaheuristic optimization algorithms, named as Simulated Kalman Filter (SKF), and single-solution Simulated Kalman Filter (ssSKF) algorithms are introduced for global optimization problems. …”
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Thesis -
17
Angle Modulated Simulated Kalman Filter Algorithm for Combinatorial Optimization Problems
Published 2016“…Inspired by the estimation capability of Kalman filter, we have recently introduced a novel estimation-based optimization algorithm called simulated Kalman filter (SKF). …”
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Article -
18
Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation
Published 2022“…The proposed algorithm is simulated for simultaneous OPF-based conflicting objectives, respectively. …”
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Thesis -
19
Predictive-reactive job shop scheduling for flexible production systems with the combination of optimization and simulation based algorithm
Published 2020“…This research will address some aspects of combining simulation and optimization-based algorithms for job-shop scheduling and rescheduling of flexible production systems. …”
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Article -
20
Opposition-based learning simulated kalman filter for Numerical optimization problems
Published 2016“…Simulated Kalman Filter (SKF) optimization algorithm is a population-based optimizer operated mainly based on Kalman filtering. …”
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