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1
Hybrid Artificial Bees Colony Algorithms For Optimizing Carbon Nanotubes Characteristics
Published 2018“…Chemical Vapor Deposition (CVD) is the most efficient method for CNTs production.However,using CVD method encounters crucial issues such as customization,time and cost.Therefore,Response Surface Methodology (RSM) is proposed for modeling and the ABC-βHC is proposed for optimization purpose to address such issues.The selected CNTs characteristics are CNTs yield and quality represented by the ratio of the relative intensity of the D and G-bands (ID/IG).Six case studies are generated from collected dataset including four cases of CNTs yield and one case of ID/IG as single objective optimization problems,while the sixth case represents multi-objective problem.The input parameters of each case are a subset from the set of input parameters including reaction temperature,duration,carbon dioxide flow rate,methane partial pressure,catalyst loading,polymer weight and catalyst weight.The models for the first three case studies were mentioned in the original work.RSM is proposed to develop polynomial models for the output responses in the other three cases and to identi significant process parameters and interactions that could affect the CNTs output responses.The developed models are validated using t-test,correlation and pattern matching.The predictive results have a good agreement with the actual experimental data.The models are used as objective functions in optimization techniques.For multi-objective optimization,this study proposes Desirability Function Approach (DFA) to be integrated with other proposed algorithms to form hybrid techniques namely RSM-DFA,ABC-DFA and ABC-βHC-DFA.The proposed algorithms and other selected well-known algorithms are evaluated and compared on their CNTs yield and quality.The optimization results reveal that ABC-βHC and ABC-βHC-DFA obtained significant results in terms of success rate,required time,iterations,and function evaluations number compared to other well-known algorithms.Significantly,the optimization results from this study are better than the results from the original work of the collected dataset.…”
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2
Hyperdize Jaya Algorithm for Harmony Search Algorithm's Parameters Selection
Published 2016“…This paper present a successful method to tune the parameters of the harmony search algorithm, which is a well-known meta-heuristic algorithm. …”
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3
Optimisation of multi-stage production-inspection stations using genetic algorithm
Published 2000“…The optimisation tool to be considered is Genetic Algorithm (GA). An introduction to the concepts of the GA and its encoding of the solutions to the problems in a genetic form and the evaluation of the resulting genetic code to give the fitness of those solutions will be discussed. …”
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Characterization of PV panel and global optimization of its model parameters using genetic algorithm
Published 2023“…The Manufacturer's Data Sheet information is used as a basis for the purpose of parameter optimization, with an average absolute error fitness function formulated; and a numerical iterative method used to solve the voltage-current relation of the PV module. …”
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Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm
Published 2018“…Design of hydraulic structures, flood warning systems, evacuation measures, and traffic management require river flood routing. A common hydrologic method of flood routing is the Muskingum method. The present study attempted to develop a three-parameter Muskingum model considering lateral flow for flood routing, coupling with a new optimization algorithm namely, Improved Bat Algorithm (IBA). …”
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Characterization of PV panel and global optimization of its model parameters using genetic algorithm
Published 2013“…The Manufacturer's Data Sheet information is used as a basis for the purpose of parameter optimization, with an average absolute error fitness function formulated; and a numerical iterative method used to solve the voltage-current relation of the PV module. …”
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On a new transmuted three-parameter lindley distribution and its applications
Published 2024“…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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Field data-based mathematical modeling by Bode equations and vector fitting algorithm for renewable energy applications
Published 2018“…From the minimal RMSE, the results show clear improvements in data fitting over other methods. The most powerful features of this method is the ability to model irregular or randomly shaped data and to be applied to any algorithms that estimating models using frequency-domain data to provide state-space or transfer function for the model.…”
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A memory-guided Jaya algorithm to solve multi-objective optimal power flow integrating renewable energy sources
Published 2025“…To ensure fair comparisons, parameter configurations for all algorithms are automated using the parameter tuning tool iterated racing (irace). …”
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Artificial neural network and inverse solution method for assisted history matching of a reservoir model
Published 2017“…This allows to directly simulate the trained neural network and avoid the use of objective function and optimization algorithm. …”
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Optimization of fast fourier transform based on twiddle factor using genetic algorithm on raspberry pi
Published 2019“…Over the years the Genetic Algorithms (GA) proved to be one of the best methods for optimization. …”
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Interactive Fuzzy Logic Interface for Enhanced Real-Time Water Quality Index Monitoring
Published 2026journal::journal article -
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Non-Parametric and Parametric Estimations of Cure Fraction Using Right-and Interval-Censored Data
Published 2011“…In this thesis, we considered two methods via the expectation maximization (EM) algorithm for cure rate estimation based on the BCH model using the two censoring types common to cancer clinical trials; namely, right and interval censoring. …”
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Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks
Published 2025thesis::doctoral thesis -
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Enhancement of new smooth support vector machines for classification problems
Published 2011“…To obtain optimal accuracy results, Uniform Design method is used to select parameter. The performance of the method is evaluated using 10-fold cross validation accuracy, confusion matrix, sensitivity and specificity. …”
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Parameter estimation of Kumaraswamy Burr type X models based on cure models with or without covariates
Published 2017“…In this thesis, we considered two methods via the classical maximum likelihood estimation (MLE) and the Bayes estimation using the Gibbs sampling (G-S) algorithm to estimate the parameters of BKBX, KBX and Beta-Weibull (BWB) models. …”
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Fuzzy methodologies for automated University timetabling solution construction and evaluation
Published 2008“…A novel approach, in which fuzzy methods are used to evaluate the end solution quality, separate from the objective functions used in solution generation, represents a significant addition to the literature. …”
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Rainfall forecasting model using machine learning methods: Case study Terengganu, Malaysia
Published 2023Article -
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Modeling and control of a Pico-satellite attitude using Fuzzy Logic Controller
Published 2010“…In this regards, a new method of Pico-satellite attitude control using Mamdani Fuzzy Logic Principles is introduced. …”
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Development of compound clustering techniques using hybrid soft-computing algorithms
Published 2006“…The neural network methods use a number of heuristics to find appropriate parametric values. …”
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