Search Results - (( parameter optimization method algorithm ) OR ( data reduction using algorithm ))
Search alternatives:
- parameter optimization »
- method algorithm »
- reduction using »
- using algorithm »
- data reduction »
-
1
An Alternative Algorithm for Soft Set Parameter Selection using Special Order
Published 2015“…Comparative analysis were performed between the proposed algorithm and the state-of-the-art parameter reduction algorithm using several soft set in terms of parameter reduction…”
Get full text
Get full text
Get full text
Conference or Workshop Item -
2
Thin Film Roughness Optimization In The Tin Coatings Using Genetic Algorithms
Published 2017“…In order to represent the process variables and coating roughness, a quadratic polynomial model equation was developed. Genetic algorithms were used in the optimization work of the coating process to optimize the coating roughness parameters. …”
Get full text
Get full text
Get full text
Article -
3
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.…”
Get full text
Get full text
Get full text
Get full text
Article -
4
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. …”
Get full text
Get full text
Thesis -
5
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.…”
Get full text
Get full text
Get full text
Article -
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. …”
Get full text
Get full text
Final Year Project -
7
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. …”
Get full text
Get full text
Thesis -
8
PSO and Linear LS for parameter estimation of NARMAX/NARMA/NARX models for non-linear data / Siti Muniroh Abdullah
Published 2017“…Typically, parameter estimation is performed using various types of Least Squares (LS) algorithms due to its stable and efficient numerical computation. …”
Get full text
Get full text
Thesis -
9
Quality of service in mobile IP networks with parametric multi-channel routing algorithms based on linear programming approach
Published 2018“…This approach tunes the parameters of the linear programming models that are used in the other algorithms by using a dynamic element. …”
Get full text
Get full text
Thesis -
10
Optimizing in-car-abandoned children’s sounds detection using deep learning algorithms / Nur Atiqah Izzati Md Fisol
Published 2023“…To address this problem, an optimized in-car-abandoned children's sounds detection model using deep learning algorithms is proposed. …”
Get full text
Get full text
Student Project -
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.…”
Get full text
Get full text
Get full text
Article -
12
-
13
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. …”
Get full text
Get full text
Get full text
Get full text
Book Chapter -
14
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.…”
Get full text
Get full text
Get full text
Article -
15
A review on soft set-based parameter reduction and decision making
Published 2017“…The soft set theory as a mathematical tool that deals with uncertainty, imprecise, and vagueness is often employed in solving decision making problem. 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. …”
Get full text
Get full text
Get full text
Get full text
Get full text
Article -
16
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). …”
Get full text
Get full text
Thesis -
17
Assisted History Matching by Using Recursive Least Square and Discrete Cosine Transform
Published 2014“…Next, RLS is applied to the parameter which has been reduced to optimize the data. …”
Get full text
Get full text
Final Year Project -
18
Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…Therefore, feature selection using Relief-f with self-adaptive Differential Evolution (rsaDE) algorithm is proposed to select the most significant features. …”
Get full text
Get full text
Thesis -
19
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.…”
Get full text
Get full text
Thesis -
20
Classification of labour pain using electroencephalogram signal based on wavelet method / Sai Chong Yeh
Published 2020“…The training and parameters selection of the machine learning algorithms are conducted using EEG data collected from ten subjects in the laboratory. …”
Get full text
Get full text
Get full text
Thesis
