Search Results - (( quality function method algorithm ) OR ( parameter evaluation method algorithm ))
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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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Single Fitness Function to Optimize Energy using Genetic Algorithms for Wireless Sensor Network
Published 2024journal::journal article -
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Enhance Cloudlet Scheduling Policy (ECSP) using cloudsim toolkit with resubmission fault tolerance mechanism
Published 2018“…This project emphasizes and evaluates the QoS parameter by performed result comparison with previous work – Improved Round Robin Cloudlet Scheduling Algorithm (IRRCSA) and Round Robin Algorithm (RRA). …”
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Channel-aware downlink scheduling for quality of service in long term evolution network
Published 2018“…These constraints comprise the use of an inefficient method to determine delay by the buffer size. In the proposed algorithm we, utilize Head of Line delay with channel-related parameters such as user data rate in addition to several pre-defined QoS tunable parameters to formulate a rule that prioritizes different user flows assigned with channel resources in order to improve delay. …”
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Power System State Estimation In Large-Scale Networks
Published 2010“…Also the WLS algorithm is modified to include Unified Power Flow Controller (UPFC) parameters. …”
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Modeling and Prediction of the mechanical properties of feedstock by cooling-slope casting process using MOJaya algorithm
Published 2024“…Hence, computational methods namely the MOJaya algorithm are utilized to model and optimize the parameters of CS to address the CS problem and forecast the performance of the feedstock. …”
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Time based internet traffic policing and shaping with Weibull traffic model / Mohd Azrul Abdullah
Published 2015“…Two important Weibull parameters which are shape and scale are measured. Based on the identified statistical parameters, a new Time Based Policing and Shaping algorithm is developed and simulated. …”
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Modeling and Prediction of The Mechanical Properties of Feedstock by Cooling-Slope Casting Process using MOJaya Algorithm
Published 2024“…Hence, computational methods namely the MOJaya algorithm are utilized to model and optimize the parameters of CS to address the CS problem and forecast the performance of the feedstock. …”
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Improvement on rooftop classification of worldview-3 imagery using object-based image analysis
Published 2019“…The accuracy of each algorithm was evaluated using LibSVM, Bayes network, and Adaboost classifier. …”
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Time based internet traffic policing and shaping with Weibull traffic model / Mohd Azrul Abdullah
Published 2015“…Two important Weibull parameters which are shape and scale are measured. Based on the identified statistical parameters, a new Time Based Policing and Shaping algorithm is developed and simulated. …”
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Interactive Fuzzy Logic Interface for Enhanced Real-Time Water Quality Index Monitoring
Published 2026journal::journal article -
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Applications of IoT and Artificial Intelligence in Water Quality Monitoring and Prediction: A Review
Published 2023Conference Paper -
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Development of wwm system using mlnn-ga for ph prediction of water quality in catchment area
Published 2021“…Artificial Neural Network or ANN is one of the methods that commonly used to predict the quality of water. …”
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Model-based hybrid variational level set method applied to object detection in grey scale images
Published 2024“…In industrial inspection, segmentation algorithms detect product defects, cracks, or anomalies for quality control and safety. …”
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Removal of BCG artefact from concurrent fMRI-EEG recordings based on EMD and PCA
Published 2017“…Methods We developed a hybrid algorithm that combines features of empirical mode decomposition (EMD) with principal component analysis (PCA) to reduce the BCG artefact. …”
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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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Enhancing riverine load prediction of anthropogenic pollutants: Harnessing the potential of feed-forward backpropagation (FFBP) artificial neural network (ANN) models
Published 2025“…Among the mathematical modelling methods employed are artificial neural networks with feed-forward backpropagation algorithms and radial basis functions. …”
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Variable Neighborhood Descent and Whale Optimization Algorithm for Examination Timetabling Problems at Universiti Malaysia Sarawak
Published 2025“…The model employs a two-level structure, where the first level uses standard soft constraints as the objective function to evaluate solution quality, while the second level dynamically adapts to faculty-specific preferences. …”
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