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1
Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…The algorithm is also preceded with careful seeding using mathematically proved to converge k-means++ algorithm. …”
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2
The compact genetic algorithm for likelihood estimator of first order moving average model
Published 2012“…Recently Genetic Algorithms (GAs) have frequently been used for optimizing the solution of estimation problems. …”
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3
An Innovative Signal Detection Algorithm in Facilitating the Cognitive Radio Functionality for Wireless Regional Area Network Using Singular Value Decomposition
Published 2011“…In order to use the algorithm effectively, users need to balance between detection accuracy and execution time. …”
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4
Ontology-based metabolic pathway prediction using saccharomyces cerevisiae data from genbank, ecocyc and kegg
Published 2006“…Thus, in order to provide better access to relevant knowledge, the knowledge of metabolic pathway should be conceptualized and formalized using appropriate knowledge representation technique. …”
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5
Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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6
Fruity vegetable recognition system using Color Histogram and BRISK features extraction / Siti Hajar Mohd Nasri
Published 2016“…In process to extract the two main features, K-means clustering algorithm is used as background subtraction method with combination of Canny’s Edge Detection and Mathematical Morphology Operation for shape extraction. …”
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7
Asset liability management model: The case of selected Islamic banks in Malaysia / Chong Hui Ling
Published 2017“…The multi-faceted objectives consist of the bank‟s expected returns and risks tolerance with constraints (also known as restraining functions to reflect the limitations placed on the Islamic bank‟s operating requirements), established using computational mathematics and algorithms with the aid of the MATLAB programming software. …”
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8
Modeling of flood water level prediction using NNARX / Fazlina Ahmat Ruslan
Published 2015“…Further, after a careful investigation into the OLS algorithm, it was shown that the ERR technique which is an essential part of the algorithm to reach model parsimony, has led the resultant model to select an incorrect model terms albeit some improvement in model selection criteria and validation method adopted in this study. …”
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9
A framework for automatic modelling of survival using fuzzy inference.
Published 2012“…In this framework, alternative methods of partitioning the input space can be selected to define the membership functions, for example by using expert knowledge, equalizer partitioning, fuzzy c-means clustering, or the combination of these techniques. …”
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10
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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11
Random forest algorithm for co2 water alternating gas incremental recovery factor prediction
Published 2020“…The aim of this paper is using an ensemble machine learning algorithm to develop a WAG incremental recovery factor predictive model that can be used by reservoir engineers to estimate WAG incremental recovery factor prior kick-off of laboratory experiments and comprehensive technical studies. …”
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12
Model input and structure selection in multivariable dynamic modeling of batch distillation column pilot plant / Ilham Rustam
Published 2015“…Further, after a careful investigation into the OLS algorithm, it was shown that the ERR technique which is an essential part of the algorithm to reach model parsimony, has led the resultant model to select an incorrect model terms albeit some improvement in model selection criteria and validation method adopted in this study. …”
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13
Detection of Epileptic EEG Signal Using Wavelet Transform and Adaptive Neuro-Fuzzy Inference System
Published 2011“…Such algorithms use brain electrical activity signals called electro encephalography (EEG) and have 2 methods of detection: visual (by specialist inspection) and automatic (by using signal processing knowledge). …”
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14
Indirect Rotor Field Oriented Control of Induction Motor With Rotor Time Constant Estimation
Published 2004“…A simple yet effective rotor time constant identification method is presented and used for updating the slip calculator used by the IRFOC algorithms. …”
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15
Ensemble model of non-linear feature selection-based Extreme Learning Machine for improved natural gas reservoir characterization
Published 2015“…The deluge of multi-dimensional data acquired from advanced data acquisition tools requires sophisticated algorithms to extract useful knowledge from such data. …”
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16
Finding the root of nonlinear function using five bracketing method / Nur Afiqah Mohamed Azhar
Published 2019“…Therefore, numerical method in the form of bracketing method is often used to find only the approximate root of the function. …”
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17
Computed tomography and echocardiography image fusion technique for cardiac images
Published 2016“…Ultrasound is used in minimally invasive cardiac procedures widely, because of its convenience and noninvasive nature. …”
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18
Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions
Published 2018“…The second technique is to solve bi-objective functions by using the BOBAT algorithm. The third technique is an integration of BOGSA with BOBAT to produce a BOGSBAT algorithm. …”
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19
Overview of metaheuristic: classification of population and trajectory
Published 2010“…Algorithms are used to find the solutions through the computer program. …”
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20
Determining the preprocessing clustering algorithm in radial basis function neural network
Published 2008“…Three types of method used in this study to find the centres include random selections, K-means clustering algorithm and also K-median clustering algorithm. …”
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