Search Results - (( initial estimation method algorithm ) OR ( parameter classification using algorithm ))
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Finite impulse response optimizers for solving optimization problems
Published 2019“…Simulated Kalman filter (SKF) algorithm is one of the algorithms under this classification. …”
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Finite impulse response optimizers for solving optimization problems
Published 2019“…Simulated Kalman filter (SKF) algorithm is one of the algorithms under this classification. …”
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Backpropagation algorithm for classification problem: academic performance prediction model for UiTM Melaka Mengubah Destini Anak Bangsa (MDAB) program. / Fadhlina Izzah Saman, Nur...
Published 2012“…Multilayer perceptrons (MLPs) is one of the topology used for processing ANN, while backpropagation algorithm is one of the most popular methods in training MLPs. …”
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Research Reports -
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Robust techniques for linear regression with multicollinearity and outliers
Published 2016“…The proposed method is formulated by incorporating robust MM-estimator and the modified generalized M-estimator (MGM) in the LRR algorithm. …”
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Hybrid ACO and SVM algorithm for pattern classification
Published 2013“…This study presents four algorithms for tuning the SVM parameters and selecting feature subset which improved SVM classification accuracy with smaller size of feature subset. …”
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Intelligent classification algorithms in enhancing the performance of support vector machine
Published 2019“…Common methods associated in tuning SVM parameters will discretize the continuous value of these parameters which will result in low classification performance. …”
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Parameter estimation of tapioca starch hydrolysis process: application of least squares and genetic algorithm
Published 2005“…The performance of genetic algorithm (GA) in nonlinear kinetic parameter estimation of topiaca starch hydrolysis was studied and compared with Gauss-Newton method. …”
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Parameter estimation in computational systems biology models: a comparative study of initialization methods in global optimization
Published 2022“…In this work, several choices of initialization methods are compared and experimental results indicated that the algorithm is sensitive to the initial value of kinetic parameters. …”
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Incremental continuous ant colony optimization for tuning support vector machine’s parameters
Published 2013“…Support Vector Machines are considered to be excellent patterns classification techniques. The process of classifying a pattern with high classification accuracy counts mainly on tuning Support Vector Machine parameters which are the generalization error parameter and the kernel function parameter.Tuning these parameters is a complex process and Ant Colony Optimization can be used to overcome the difficulty. …”
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Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman
Published 2019“…In this HPSO algorithm, totally seven particles positions are initialized. …”
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Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak
Published 2019“…The fourth stage is to design evaluation methodology of Max-Min Rule-Based Classification Algorithm using classifier model. Finally, both algorithms are validated against the findings in various literatures. …”
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Optimizing support vector machine parameters using continuous ant colony optimization
Published 2012“…Hence, in applying Ant Colony Optimization for optimizing Support Vector Machine parameters, which are continuous parameters, there is a need to discretize the continuous value into a discrete value.This discretization process results in loss of some information and, hence, affects the classification accuracy and seek time.This study proposes an algorithm to optimize Support Vector Machine parameters using continuous Ant Colony Optimization without the need to discretize continuous values for Support Vector Machine parameters.Seven datasets from UCI were used to evaluate the performance of the proposed hybrid algorithm.The proposed algorithm demonstrates the credibility in terms of classification accuracy when compared to grid search techniques.Experimental results of the proposed algorithm also show promising performance in terms of computational speed.…”
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Fuzzy modeling using Bat Algorithm optimization for classification
Published 2018“…A Sazonov Engine which is a fuzzy java engine is use to apply Bat Algorithm in the experiment. The value of parameter is already set to use when applying every dataset in an experiment. …”
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Undergraduates Project Papers -
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Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System
Published 2020“…IPJAYA in this study was used to update the C and gamma parameters of the support vector machine (SVM). …”
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Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm
Published 2023“…Genetic Algorithm (GA) is used to search for the best parameter of SVM classification by using combination of random and pre-populated genomes from Pre-Populated Database (PPD). …”
Conference Paper -
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Comparison between Newton’s Method and a new Scaling Newton Method / Ramizah Baharuddin
Published 2021“…Newton's Method also called the Newton-Raphson method is a recursive algorithm for approximating the root of a differentiable function. …”
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Classification of tropical rainforest using different classification algorithm based on remote sensing imagery: A study of Gunung Basor
Published 2019“…Thehighest accuracy for classification map of Gunung Basor is by using maximum likelihood algorithm with an accuracy of 82.90%. …”
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Undergraduate Final Project Report -
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Comparison of Logistic Regression, Random Forest, SVM, KNN Algorithm for Water Quality Classification Based on Contaminant Parameters
Published 2024“…This study compares four machine learning algorithms Logistic Regression, Random Forest, Support Vector Machine (SVM), and K-Nearest Neighbors (KNN) in water quality classification based on contaminant parameters. …”
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An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani
Published 2015“…The urban growth images obtained are analysed to improve existing classification algorithms. The improved algorithm is constructed by adding new parameter and classification rule to existing algorithm. …”
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