Search Results - (( data reduction methods algorithm ) OR ( parameter optimization method algorithm ))*
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1
An Alternative Algorithm for Soft Set Parameter Selection using Special Order
Published 2015“…This paper proposed a parameter reduction algorithm, known as 3C algorithm, to circumvent the false frequent object in reduction. …”
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Conference or Workshop Item -
2
Thin Film Roughness Optimization In The Tin Coatings Using Genetic Algorithms
Published 2017“…Optimization is important to identify optimal parameters in many disciplines to achieve high quality products including optimization of thin film coating parameters. …”
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3
Mobility management schemes based on multiple criteria for optimization of seamless handover in long term evolution networks
Published 2014“…The results demonstrated that our proposed method results in significant reductions of HOF, HOPP and packet loss ratio (PLR) compared to the conventional HHO and enhanced weighted performance HO parameter optimization (EWPHPO) algorithm. …”
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4
Hybridization of nonlinear sine cosine and safe experimentation dynamics algorithms for solving control engineering optimization problems
Published 2024“…The empirical assessment of these proposed methods encompasses a diverse set of 23 benchmark functions, demonstrating their efficacy comparable to well-established metaheuristic algorithms such as as the Grey Wolf Optimizer (GWO), Multi-Verse Optimization (MVO), Sine Cosine Algorithm (SCA), Ant Lion Optimizer (ALO), Moth-Flame Optimization Algorithm (MFO), and Grasshopper Optimization Algorithm (GOA). …”
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Thesis -
5
PSO and Linear LS for parameter estimation of NARMAX/NARMA/NARX models for non-linear data / Siti Muniroh Abdullah
Published 2017“…Results suggest that the PSO algorithm is viable alternative to other established algorithms for LLS parameter estimation. …”
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6
Assisted History Matching by Using Genetic Algorithm and Discrete Cosine Transform
Published 2014“…Apart from that, the manual way consume too much time, especially when dealing with thousands of well parameters. Hence, this project, which propose the usage of assisted history matching technique with Genetic Algorithm (GA) as the optimization tool and Discrete Cosine Transform (DCT) as the parameter reduction method is carried out in order to achieve the objective of minimizing the time taken to do history matching. …”
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Final Year Project -
7
Enhancing Wearable-Based Human Activity Recognition with Binary Nature-Inspired Optimization Algorithms for Feature Selection
Published 2026“…The experiment results show how these algorithms could be used to improve methods for recognizing human activities using wearables technology, such as feature selection, parameter adjustment, and model optimization.…”
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Neural network modeling and optimization for spray-drying coconut milk using genetic algorithm and particle swarm optimization
Published 2022“…The ANN model is further improved using GA and PSO. Each algorithm has its own parameters and is further optimized using RSM. …”
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9
Modeling And Optimization Of Physical Vapour Deposition Coating Process Parameters For Tin Grain Size Using Combined Genetic Algorithms With Response Surface Methodology
Published 2015“…Additionally,analysis of variance(ANOVA) was used to determine the significant factors influencing resultant TiN coating grain size.Based on that,a quadratic polynomial model equation was developed to represent the process variables and coating grain size.Then,in order to optimize the coating process parameters, genetic algorithms (GAs) were combined with the RSM quadratic model and used for optimization work.Finally,the models were validated using actual testing data to measure model performances in terms of residual error and prediction interval (PI).The result indicated that for RSM,the actual coating grain size of validation runs data fell within the 95% (PI) and the residual errors were less than 10 nm with very low values, the prediction accuracy of the model is 96.09%.In terms of optimization and reduction the experimental data,GAs could get the best lowest value for grain size then RSM with reduction ratio of ≈6%, ≈5%, respectively.…”
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10
Quality of service in mobile IP networks with parametric multi-channel routing algorithms based on linear programming approach
Published 2018“…Furthermore, Optimized Parametric Topology Control Routing algorithm performs significantly better than Triangular Routing Method and Change Foreign Agent Algorithm. …”
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11
A new model for iris data set classification based on linear support vector machine parameter's optimization
Published 2020“…In this study, we proposed a newly mode for classifying iris data set using SVM classifier and genetic algorithm to optimize c and gamma parameters of linear SVM, in addition principle components analysis (PCA) algorithm was use for features reduction.…”
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Optimizing in-car-abandoned children’s sounds detection using deep learning algorithms / Nur Atiqah Izzati Md Fisol
Published 2023“…Both models' parameters are optimized to achieve optimal performance. …”
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Student Project -
14
Data-driven PID tuning for liquid slosh-free motion using memory-based SPSA algorithm
Published 2018“…Tis memory-based SPSA (M-SPSA) algorithm has a capability to obtain better optimization accuracy than the conventional SPSA, since it is able to keep the best design parameter during the tuning process. …”
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Book Chapter -
15
A review on soft set-based parameter reduction and decision making
Published 2017“…It has been widely used to identify irrelevant parameters and make reduction set of parameters for decision making in order to bring out the optimal choices. …”
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16
Intelligence Integration Of Particle Swarm Optimization And Physical Vapour Deposition For Tin Grain Size Coating Process Parameters
Published 2016“…Additionally,analysis of variance (ANOVA) was used to determine the significant factors influencing resultant TiN coating grain size.Based on that,a quadratic polynomial model equation was developed to represent the process variables and coating grain size.Then,in order to optimize the coating process parameters,genetic algorithms (GAs) were combined with the RSM quadratic model and used for optimization work.Finally,the models were validated using actual testing data to measure model performances in terms of residual error and prediction interval (PI).The result indicated that for RSM,the actual coating grain size of validation runs data fell within the 95% (PI) and the residual errors were less than 10 nm with very low values, the prediction accuracy of the model is 96.09%.In terms of optimization and reduction the experimental data,GAs could get the best lowest value for grain size then RSM with reduction ratio of ≈6%, ≈5%, respectively.…”
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Article -
17
Assisted History Matching by Using Recursive Least Square and Discrete Cosine Transform
Published 2014“…Thus, this project is carried to do assisted history matching and to determine whether Recursive least square as optimization method and Discrete cosine transform as parameter reduction method can be combined or not. …”
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Final Year Project -
18
Development of cost reduction mathematical model for natural gas transmission network system
Published 2012“…Therefore, the data clearly exhibit that the proposed method provides a solution that was nearer to an optimized network.…”
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Thesis -
19
Improved genetic algorithm for direct current motor high speed controller implemented on field programmable gate array
Published 2019“…There are many researches have been done to optimize PI controller based evolutionary algorithm, such as Genetic Algorithm (GA). …”
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Thesis -
20
Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…Also, self-adaptive scaling factor and crossover probability control parameters are introduced to diminish time of finding an optimal parameter to produce the best population. …”
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Thesis
