Search Results - (( developing function method algorithm ) OR ( _ application model algorithm ))
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1
Semiparametric inference procedure for the accelarated failure time model with interval-censored data
Published 2019“…The main contribution of this research is developing statistical approaches, and introducing new algorithms and resampling methods for analysing interval-censored data through AFT models.…”
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2
Real time nonlinear filtered-x lms algorithm for active noise control
Published 2012“…The NLFXLMS algorithm is a stochastic gradient algorithm that incorporates the derivative of a nonlinear plant model which is represented by the scaled error function (SEF) in the controller design. …”
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3
Nlfxlms and thf-nlfxlms algorithms for wiener-hammerstein nonlinear active noise control
Published 2016“…The development of these algorithms becomes the first and second objectives of this research. …”
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4
A study on regional GDP forecasting analysis based on radial basis function neural network with genetic algorithm (RBFNN-GA) for Shandong economy
Published 2022“…This study uses the genetic algorithm radial basis, neural network model, to make judgments on the relationships contained in this sequence and compare and analyze the prediction effect and generalization ability of the model to verify the applicability of the genetic algorithm radial basis, neural network model, based on the modeling of historical data, which may contain linear and nonlinear relationships by itself, so this study uses the genetic algorithm radial basis, neural network model, to make, compare, and analyze judgments on the relationships contained in this sequence.…”
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5
Development of a new method of crack modeling and prediction algorithm
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Proceeding Paper -
6
Improved expectation maximization algorithm for Gaussian mixed model using the kernel method
Published 2013“…We show via simulation that the technique improves the performance of the algorithm. Secondly, we developed a procedure for determining the order of the Gaussian mixed model using the log-likelihood function and the Akaike information criteria. …”
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7
Long term energy demand forecasting based on hybrid, optimization: Comparative study
Published 2012“…The objective of this research is to develop a long term energy demand forecasting model that used hybrid optimization.To accomplish this goal, a hybrid algorithm that combined a genetic algorithm and a local search algorithm method has been developed to overcome premature convergence.Model performances of hybrid algorithm were compared with former single algorithm model in estimating parameter values of an objective function to measure the goodness-of-fit between the observed data and simulated results.Averages error between two models was adopt to select the proper model for future projection of energy demand.…”
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8
A Descent Three-Term Conjugate Gradient Direction For Problems Of Unconstrained Optimization With Application
Published 2026“…The development of this new algorithm is based on the findings of recently introduced generalized RMIL CG technique. …”
preprint -
9
State of charge estimation for lithium-ion battery based on random forests technique with gravitational search algorithm
Published 2023Conference Paper -
10
Estimation of photovoltaic models using an enhanced Henry gas solubility optimization algorithm with first-order adaptive damping Berndt-Hall-Hall-Hausman method
Published 2024“…To address the existing theoretical gap, this study focused on developing an objective function that accurately estimates the initial root parameters of Photovoltaic (PV) models. …”
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11
A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…Then, this study aims to optimize the hyperparameters of the developed DNN model using the Arithmetic Optimization Algorithm (AOA) and, lastly, to evaluate the performance of the newly proposed deep learning model with Simulated Kalman Filter (SKF) algorithm in solving image encryption application. …”
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12
The compact genetic algorithm for likelihood estimator of first order moving average model
Published 2012“…The poor behavior of genetic algorithms in some problems, sometimes attributed to design operators, has led to the development of other types of algorithms. …”
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13
Development of multi-objective optimization methods for integrated scheduling of handling equipment (AGVs, QCs, SP-AS/RS) in automated container terminals
Published 2012“…Therefore, two meta-heuristic algorithms, namely genetic algorithm (GA) and simulated annealing (SA) algorithm, were developed to optimize the integrated scheduling of handling equipment. …”
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14
Effort Estimation Model for Function Point Measurement
Published 2007“…This research work has generated an algorithmic effort estimation model for function points measurement. …”
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15
Field data-based mathematical modeling by Bode equations and vector fitting algorithm for renewable energy applications
Published 2018“…The modification is derived from the familiar VF algorithm as a robust numerical method. This development increases the application range of the VF algorithm for modeling not only in the frequency domain but also for all power curves. …”
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16
New Quasi-Newton Equation And Method Via Higher Order Tensor Models
Published 2010“…The comparison between this new method with that of the method developed by Xiao et al. (2008) shows better performance in numerical results for the new method. …”
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17
Neural network modeling and optimization for spray-drying coconut milk using genetic algorithm and particle swarm optimization
Published 2022“…Integration of global search algorithm into ANN model further improved the model performance. …”
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18
Enhancement of Ant System Algorithm for Course Timetabling Problem
Published 2009“…This research starts with developing an algorithm based on original concept of Ant System Algorithm. …”
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19
DESIGN AND EVALUATION OF RESOURCE ALLOCATION AND JOB SCHEDULING ALGORITHMS ON COMPUTATIONAL GRIDS
Published 2012“…The issue is not only to develop new algorithms, but also to evaluate them on an experimental computational grid, using synthetic and real workload traces, along with the other existing job scheduling algorithms. …”
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20
Improvement and application of particle swarm optimization algorithm
Published 2025“…Finally, real-world tests are performed to verify the proposed Algorithm's efficacy compared to existing optimization methods. …”
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