Search Results - (( a distribution based algorithm ) OR ( (parameter OR parameters) simulation model algorithm ))

GENETIC ALGORITHM WITH DEEP NEURAL NETWORK SURROGATE FOR THE OPTIMIZATION OF ELECTROMAGNETIC STRUCTURE by MOHAMMED SHARIFF, NUR ATIQAH

“…The behavior of Genetic Algorithm (GA) where it generates and evolves the parameters towards a high-quality solution gives an advantage in obtaining ideal combination of parameters to fit in with the simulation. …”
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Time based internet traffic policing and shaping with Weibull traffic model / Mohd Azrul Abdullah by Abdullah, Mohd Azrul

“…Based on the identified statistical parameters, a new Time Based Policing and Shaping algorithm is developed and simulated. …”
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Semiparametric inference procedure for the accelarated failure time model with interval-censored data by Karimi, Mostafa

“…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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Time based internet traffic policing and shaping with Weibull traffic model / Mohd Azrul Abdullah by Abdullah, Mohd Azrul

“…Based on the identified statistical parameters, a new Time Based Policing and Shaping algorithm is developed and simulated. …”
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An enhanced segment particle swarm optimization algorithm for kinetic parameters estimation of the main metabolic model of Escherichia coli by Mohammed Adam, Kunna, Tuty Asmawaty, Abdul Kadir, Muhammad Akmal, Remli, Noorlin, Mohd Ali, Kohbalan, Moorthy, Noryanti, Muhammad

“…In addition, building a kinetic model requires the estimation of the kinetic parameters, but kinetic parameters estimation in kinetic modeling is a difficult task due to the nonlinearity of the model. …”
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Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari by Satari, Siti Zanariah

“…Here, we introduce a measure of similarity based on the circular distance and obtain a cluster tree using the single linkage clustering algorithm. …”
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Slice sampler algorithm for generalized pareto distribution by Rostami, Mohammad, Adam, Mohd Bakri, Yahya, Mohamed Hisham, Ibrahim, Noor Akma

“…In this paper, we developed the slice sampler algorithm for the generalized Pareto distribution (GPD) model. …”
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Automatic control of flotation process using computer vision by Saravani, Ali Jahed

“…A froth model correlating the image variables to process variables and a prediction system estimating the metallurgical parameters based on image variables were then developed by using a neural network structure. …”
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Fair bandwidth distribution marking and scheduling algorithm in network traffic classification by Al-Kharasani, Ameen Mohammed Abdulkarem

“…Second, propose an Optimized Time Sliding Window based Three Colour Marker. Finally, propose a new method of obtaining optimal parameters dropping functions for Random Early Detection (RED) algorithm. …”
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On a new transmuted three-parameter lindley distribution and its applications by Xi, Yuhang, Lu, Hezhi, Liang, Fei

“…In this paper, a new transmuted three-parameter Lindley distribution (TTHPLD) is established using the transmutation map method, which includes the Lindley distribution, two-parameter Lindley distribution, transmuted two-parameter Lindley distribution and three-parameter Lindley distribution as special cases. …”
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Kalman filter based impedance parameter estimation for transmission line and distribution line by Siti Nur Aishah, Mohd Amin

“…Therefore, a detailed study on developing and evaluating the new algorithms for transmission line parameter estimation is considered in this thesis. …”
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A new Gompertz-three-parameter-lindley distribution for modeling survival time data by Liang, Fei, Lu, Hezhi, Xi, Yuhang

“…Moreover, a new regression model based on the proposed distribution is presented. …”
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Bayesian inference for the bivariate extreme model by Mohd Amin, Nor Azrita, Adam, Mohd Bakri

“…The model is used in a Bayesian framework where no information of prior is available on unknown model parameters. …”
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An augmented sequential MCMC procedure for particle based learning in dynamical systems by Javvad ur Rehman, M., Dass, S.C., Asirvadam, V.S.

“…Particle-based parameter learning methods form a well-known class of procedures for obtaining inference in state space models where a collection of particles are used to represent the posterior distributions of parameters. …”
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Competing risks for reliability analysis using Cox’s model by Mohamed Elfaki, Faiz Ahmed, Daud, Isa, Ibrahim, Nor Azowa, Abdullah, M. Y., Usman, Mustofa

“…Design/methodology/approach – The parameters of the models have been estimated by method of maximum likelihood based on EM algorithm. …”
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Hybrid meta-heuristic algorithm for solving multi-objective aggregate production planning in fuzzy environment by Kalaf, Kalaf, Bayda Atiya

“…For these proposed approaches, this study adopted a hybridization of a fuzzy programming, modify simulated annealing, and simplex downhill (SD) algorithm called Fuzzy-MSASD to resolve multiple objective linear programming APP problems in a fuzzy environment. …”
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A firefly algorithm based hybrid method for structural topology optimization by Gebremedhen, H.S., Woldemichael, D.E., Hashim, F.M.

“…In this paper, a firefly algorithm based hybrid algorithm through retaining global convergence of firefly algorithm and ability to generate connected topologies of optimality criteria (OC) method is proposed as an alternative method to solve stress-based topology optimization problems. …”
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Location determination using radio frequency RSSI and deterministic algorithm by Hussin, A.G., Hassan, S.F., Zubairi, Y.Z., Zaharim, A., Sopian, K.

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Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares by Uraibi, Hassan Sami

“…To rectify this problem, we propose a Dynamic Robust Bootstrap-LTS based (DRBLTS) algorithm where the percentage of outliers in each bootstrap sample is detected. …”
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Parameter estimation of Kumaraswamy Burr type X models based on cure models with or without covariates by Yusuf, Madaki Umar

“…Based on the results obtained, the KBX distribution has provided a better fit compared to the BKBX, the baseline BX, and non-nested models based on the model selection criteria using the MLE.…”
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