Search Results - (( parameter estimation study algorithm ) OR ( parameter evaluation path algorithm ))
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1
Reliability performance evaluation and integration of routing algorithm in shuffle exchange with minus one stage
Published 2012“…These routing algorithms are Zero X, Zero Y, ZeroYbit, ZeroXbit, Sequential Increasing and Sequential Decreasing Algorithm. …”
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2
Genetic algorithm for control and optimisation of exothermic batch process
Published 2013“…Nevertheless, these methods require huge batch of data for tuning its parameters. Therefore, genetic algorithm (GA) is proposed in this work since precise mathematical model is not required. …”
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3
Design of self-tuning minimum effort active noise control with feedback inclusion architecture
Published 2009“…The controller design and implementation are evaluated in terms of the level of cancellation at the observer through simulation studies for various values of modified effort weighting parameter in the range ⩽0γ⩽1. …”
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4
Channel Modeling and Direction-of-Arrival Estimation in Mobile Multiple-Antenna Communication Systems
Published 2005“…Estimated parameters from recent measurements ([PMFOO]) are compared with estimated parameters from model generated waveforms as well as theoretical distribution of received signal's angular spread. …”
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5
Evaluation of robot path planning algorithms in global static environments: genetic algorithm vs ant colony optimization algorithm / Nohaidda Sariff and Norlida Buniyamin
Published 2010“…Performances between both algorithms were compared and evaluated in terms of speed and number of iterations that each algorithm takes to find an optimal path within several selected environments. …”
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6
A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments
Published 2013“…Sampling-based motion planning is a class of randomized path planning algorithms with proven completeness. …”
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7
Cognitive map approach for mobility path optimization using multiple objectives genetic algorithm
Published 2023Subjects:Conference Paper -
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A multi-objective parametric algorithm for sensor-based navigation in uncharted terrains
Published 2023“…These parameters are designed carefully to cover different requirements of the path planner. …”
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Performance comparison between genetic algorithm and ant colony optimization algorithm for mobile robot path planning in global static environment / Nohaidda Sariff
Published 2011“…Subsequently, both algorithms were applied to the test environments. Finally, the performances of both algorithms were analyzed and evaluated based on the required criteria. …”
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10
An Experiment of Ant Algorithms : Case Study of Kota Kinabalu Central Town
Published 2005“…The objectives of this study are to explore and evaluate the Ant System (AS) algorithm and Ant Colony System (ACS) algorithm in finding shortest paths. …”
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11
Performance analysis of ZigBeePRO network using shortest path algorithm for Distributed Renewable Generation
Published 2021“…Due to this polarization effect, the brick-built type cabin at the DRG site is a consequence of a higher propagation path loss than the Iron (III)-made cabin. The other performance parameters, including network throughput, data loss, and ZigBeePRO collision, are also evaluated.…”
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12
Estimation in spot welding parameters using genetic algorithm
Published 2007“…In this study, parameter of spot welding estimate using computer simulation. …”
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13
LASSO-type estimations for threshold autoregressive and heteroscedastic time series models.
Published 2020“…Furthermore, the ensemble algorithms of BCD-BEA perform better in terms of correctly estimating the number of thresholds in simulation studies, and in identifying important thresholds in case studies compared to the ensemble algorithms of GLAR-BEA. …”
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14
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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15
All-pass filtered x least mean square algorithm for narrowband active noise control
Published 2018“…The performance evaluation in terms of convergence speed of the proposed algorithm is validated with standard ANC without secondary path modelling. …”
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16
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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17
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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18
Parameter estimation of tapioca starch hydrolysis process: application of least squares and genetic algorithm
Published 2005“…The performance of genetic algorithm (GA) in nonlinear kinetic parameter estimation of topiaca starch hydrolysis was studied and compared with Gauss-Newton method. …”
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19
Using the evolutionary mating algorithm for optimizing deep learning parameters for battery state of charge estimation of electric vehicle
Published 2023“…This paper presents the application of a recent metaheuristic algorithm namely Evolutionary Mating Algorithm (EMA) for optimizing the Deep Learning (DL) parameters to estimate the state of charge (SOC) of a battery for an electric vehicle in the real environment. …”
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20
Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach
Published 2022“…This research is mainly aimed at introducing a deep learning approach to solve chaotic system parameter estimates like the Lorenz system. The reason for the study is that because of its dynamic instability, the parameter of the chaotic system cannot be easily estimated. …”
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