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1
Estimation Of Weibull Parameters Using Simulated Annealing As Applied In Financial Data
Published 2023“…However, the selection of the most suitable estimators is still a challenging task. The present study proposes a simulated annealing algorithm (SA) in estimating the parameters of Weibull distribution with application to modified internal rate of return data (MIRR).The objective is to examine the investment potential of the shari’ah compliance companies of the Malaysia property sector (MPS). …”
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2
Design Optimization of 3-Phase Rectifier Power Transformers by Genetic Algorithm and Simulated Annealing
Published 2008“…Two non-linear programming techniques, GA and SA are applied for the estimation of transformer design parameters and the results are compared. …”
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3
Design Optimization of 3-phase rectifier power transformers by Genetic Algorithm and Simulated Annealing
Published 2008“…Two non-linear programming techniques, GA and SA are applied for the estimation of transformer design parameters and the results are compared. …”
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4
Design Optimization of 3-phase rectifier power transformers by Genetic Algorithm and Simulated Annealing
Published 2008“…Two non-linear programming techniques, GA and SA are applied for the estimation of transformer design parameters and the results are compared. …”
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5
Estimation of optimal machining control parameters using artificial bee colony
Published 2013“…From the experimental results, the performance of ABC was much superior where the estimated minimum R a value was 28, 42, 45, 2 and 0.9 % lower compared to actual machining, regression, artificial neural network (ANN), genetic algorithm (GA) and simulated annealing (SA) respectively.…”
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6
A Hybrid of Particle Swarm Optimization and Harmony Search to Estimate Kinetic Parameters in Arabidopsis thaliana
Published 2020“…Three performance measurements are used in this paper to evaluate the proposed PSOHS: the standard deviation, nonlinear least squared error, and computational time. The proposed algorithm outperformed the other two methods, namely Simulated Annealing and the downhill simplex method, and proved that PSOHS is a more suitable algorithm for estimating kinetic parameter values.…”
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7
Image clustering comparison of two color segmentation techniques
Published 2010“…Finally, the algorithm found, which would solve the image segmentation problem.…”
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8
Automatic Number Plate Recognition on android platform: With some Java code excerpts
Published 2016“…On the other hand, the traditional algorithm using template matching only obtained 83.65% recognition rate with 0.97 second processing time. …”
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Book -
9
A Novel Hybrid Deep Learning Model Based on Simulated Annealing and Cuckoo Search Algorithms for Automatic Radiomics-Based COVID-19 Diagnosis
Published 2025“…To further enhance COVID-19 lesion estimation, novel optimization strategies, including a hybrid simulated annealing-cuckoo search (SA-CS) algorithm, are introduced alongside the original SA method. …”
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10
Development of seven segment display recognition using TensorFlow on Raspberry Pi
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Proceeding Paper -
11
Modeling The Modified Internal Rate Of Return (Mirr) For Long-Term Investment Strategy By The Assumption Of Gamma Distribution
Published 2023“…Alternative approaches such as the Simulated Annealing (SA) algorithm, which maximizes the log-likelihood function, and Bayesian MCMC estimation are considered. …”
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12
Some families of count distributions for modelling zero-inflation and dispersion / Low Yeh Ching
Published 2016“…A Monte Carlo simulation technique is examined and employed to overcome the computational issues arising from the intractability of the probability mass function of some mixed Poisson distributions. For parameter estimation, the simulated annealing global optimization routine and an EM-algorithm type approach for maximum likelihood estimation are studied. …”
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13
A multi-period scheduling of dynamic cellular manufacturing systems in the presence of cost uncertainty
Published 2016“…To solve the model, a hybrid genetic and simulated annealing algorithms is developed because of the high potential of outcomes to be trapped in the local optima. …”
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