Search Results - (( using classification problems algorithm ) OR ( evolution simulation approach algorithm ))
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1
Queen-bee evolution approach to prc-based papr reduction for ofdm systems
Published 2011“…The thesis proposed the adoption of Queen-bee Evolution approach for Genetic Algorithm (QBEGA) concept to improve the Genetic Algorithm for generating suboptimum peak reduction carriers (PRCs) for the orthogonal frequency division multiplexing (OFDM) systems employing a large number of sub-channels as contributed by Tan (2003a). …”
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2
Differential evolution technique of HEPWM for three-phase voltage source inverter
Published 2016“…This paper presents the execution of Differential Evolution (DE) algorithm in order to understand the principle operation of Harmonic Elimination Pulse-Width Modulation (HEPWM) switching technique. …”
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3
Dengue classification system using clonal selection algorithm / Karimah Mohd
Published 2012“…This project can be improved by making a comparative study on Artificial Immune System and other techniques or algorithms used to solve dengue classification problems.…”
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4
Harmonic Elimination Pulse Width Modulation Using Differential Evolution Technique For Three Phase Voltage Source Inverter
Published 2018“…Explanation of DE algorithm execution is given, and the best approach of mutation strategy selection used in DE has been investigated. …”
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5
An improve unsupervised discretization using optimization algorithms for classification problems
Published 2024“…This paper addresses the classification problem in machine learning focusing on predicting class labels for datasets with continuous features. …”
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An improve unsupervised discretization using optimization algorithms for classification problems
Published 2024“…This paper addresses the classification problem in machine learning, focusing on predicting class labels for datasets with continuous features. …”
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7
Resource allocation in coordinated multipoint long term evolution-advanced networks
Published 2015“…Simulation study shows that the ORA algorithm improves the network sum-rate and fairness index up to 70% and 25%, respectively and reduces the average transmit power by 41% in relative to LRA algorithm. …”
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8
Evolution of RF-signal cognition for wheeled mobile robots using pareto multi-objective optimization
Published 2009“…This article describes a simulation model in which a multi-objective approach is utilized for evolving an artificial neural networks (ANNs) controller for an autonomous mobile robot. …”
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9
Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd
Published 2022“…One of the most powerful machine learning methods to handle classification problems is the decision tree. There are various decision tree algorithms, but the most commonly used are Iterative Dichotomiser 3 (ID3), CART, and C4.5. …”
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10
A Hybrid of Ant Colony Optimization Algorithm and Simulated Annealing for Classification Rules
Published 2013“…Classification rule induction is one of the problems solved by the Ant-miner algorithm, a variant of ACO, which was initiated by Parpinelli in 2001. …”
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11
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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12
Selective Harmonics Elimination PWM (SHEPWM)Using Differential Evolution Approach
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13
Classification for large number of variables with two imbalanced groups
Published 2020“…Several approaches have been devoted to study such problems using linear and non-linear classification rules, but limited to group imbalance rather than the combination of both problems. …”
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14
Improved Differential Evolution-Based MPPT Algorithm Using SEPIC for PV Systems Under Partial Shading Conditions and Load Variation
Published 2018“…Thus, an improved global search space differential evolution algorithm for tracking the GMPP is introduced in this paper. …”
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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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16
An adaptive ant colony optimization algorithm for rule-based classification
Published 2020“…Ant-Miner is a variant of ant colony optimisation and a prominent intelligent algorithm widely use in rules-based classification. …”
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17
Evolving controllers for simulated car racing using differential evolution
Published 2013“…The Differential Evolution (DE) algorithm is combined with Feed-forward Artificial Neural Networks (FFANNs) to generate the required intelligent controllers in a well-known car racing game, namely The Open Racing Car Simulator (TORCS). …”
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Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model
Published 2018“…Expectation maximization (EM) is one of the representatives clustering algorithms which have broadly applied in solving classification problems by improving the density of data using the probability density function. …”
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Attribute related methods for improvement of ID3 Algorithm in classification of data: A review
Published 2020“…Decision tree is an important method in data mining to solve the classification problems. There are several learning algorithms to implement the decision tree but the most commonly-used is ID3 algorithm. …”
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Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition
Published 2017“…The problems in applying unsupervised learning/clustering is that this method requires teacher during the classification process and it has to learn independently which may lead to poor classification. …”
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