Search Results - (( using classification modeling algorithm ) OR ( basic iteration method algorithm ))
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Augmentation of basic-line-search and quick-simplex-method algorithms to enhance linear programming computational performance
Published 2021“…The LP’s application is need to be further computed with a technique and Simplex algorithm is the one that commonly used. The Simplex algorithm has three stages of computation namely initialization, iterative calculation and termination. …”
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Thesis -
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Schelkunoff array synthesis methods using adaptive-iterative algorithm
Published 2003“…Basically, this algorithm is a combination of iterative algorithm with adaptive algorithm. …”
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Quarter-sweep arithmetic mean iterative algorithm to solve fourth-order parabolic equations
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Conference or Workshop Item -
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Solving Blasius equation using semi analytic iterative method / Nurul Atikah Halmi and Nur Azyyati Ayob
Published 2018“…Variational iterative method (VIM) and Iteration method existing results was chosen to be compare with SAIM expectation outcomes. …”
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Flowshop scheduling using artificial bee colony (ABC) algorithm with varying onlooker bees approaches
Published 2015“…If iteration available is long, method 3+0+0 is more appropriate, otherwise method 2+1+0 is the best choice. …”
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Thesis -
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DESIGN AND IMPLEMENTATION OF RIPEMD-160 HASH FUNCTION USING VERILOG HDL
Published 2022“…This project proposes to design an iterative method of RIPEMD-160 in order to investigate the security algorithm and its implementation. …”
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Final Year Project Report / IMRAD -
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A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network
Published 2014“…In the present study, the results of the implementation of a novel hybrid feature selection-classification model using the above mentioned methods are presented. …”
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DESIGN AND IMPLEMENTATION OF RIPEMD-160 ALGORITHM ON RECONFIGURABLE HARDWARE
Published 2019“…The RIPEMD-160 can improve the security in storing information. This project used iterative method to investigate the security algorithm and implemented the algorithm. …”
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Final Year Project Report / IMRAD -
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Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model
Published 2018“…EM and K-means clustering algorithms are used to cluster the multi-class classification attribute according to its relevance criteria and afterward, the clustered attributes are classified using an ensemble random forest classifier model. …”
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Studies on flat CORDIC implementation in field programmable gate arrays (FPGA) / Meera Subramaniam
Published 2004“…This work presents a modification to the previous Signed Digit (SD) Generation algorithm and a comparison with the previous method. …”
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Thesis -
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Data Analysis using Particle Swarm Optimization Algorithm
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Final Year Project / Dissertation / Thesis -
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An adaptive ant colony optimization algorithm for rule-based classification
Published 2020“…Various classification algorithms have been developed to produce classification models with high accuracy. …”
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Predicting breast cancer using ant colony optimisation / Siti Sarah Aqilah Che Ani
Published 2021“…This study implements a machine learning algorithm called Ant Colony Optimization (ACO) algorithm to develop an accurate classification model for predicting breast cancer cells. …”
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Student Project -
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Formulating new enhanced pattern classification algorithms based on ACO-SVM
Published 2013“…ACO originally deals with discrete optimization problem.In applying ACO for solving SVM model selection problem which are continuous variables, there is a need to discretize the continuously value into discrete values.This discretization process would result in loss of some information and hence affects the classification accuracy and seeking time.In this algorithm we propose to solve SVM model selection problem using IACOR without the need to discretize continuous value for SVM.The second algorithm aims to simultaneously solve SVM model selection problem and selects a small number of features.SVM model selection and selection of suitable and small number of feature subsets must occur simultaneously because error produced from the feature subset selection phase will affect the values of SVM model selection and result in low classification accuracy.In this second algorithm we propose the use of IACOMV to simultaneously solve SVM model selection problem and features subset selection.Ten benchmark datasets were used to evaluate the proposed algorithms.Results showed that the proposed algorithms can enhance the classification accuracy with small size of features subset.…”
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Classification model for water quality using machine learning techniques
Published 2015“…In assessing the result, the Lazy model using K Star algorithm was the best classification model among the five models had the most outstanding accuracy of 86.67%. …”
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Classification of Diabetes Mellitus (DM) using Machine Learning Algorithms
Published 2021“…Whereas for the German Frankfurt dataset, best DM classification model was found using Random Forest algorithm with an accuracy of 98.77%.…”
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Final Year Project
