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A modified fuzzy min-max neural network with a genetic-algorithm-based rule extractor for pattern classification
Published 2010“…The first stage consists of a modified fuzzy min-max (FMM) neural-network-based pattern classifier, while the second stage consists of a genetic-algorithm (GA)-based rule extractor. …”
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Individual And Ensemble Pattern Classification Models Using Enhanced Fuzzy Min-Max Neural Networks
Published 2014“…Owing to a number of salient features which include the ability of learning incrementally and establishing nonlinear decision boundary with hyperboxes, the Fuzzy Min-Max (FMM) network is selected as the backbone for designing useful and usable pattern classification models in this research. …”
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Modern fuzzy min max neural networks for pattern classification
Published 2019“…Among these algorithms, Fuzzy Min Max (FMM) neural network algorithm has been proven to be one of the premier neural networks for undertaking the pattern classification problems. …”
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Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm
Published 2008“…The prototype system, known as Java Plagiarism Detection System (JPDS) implements the Greedy-String-Tiling algorithm to detect similarities among tokens in a Java source code files. …”
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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. …”
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A Comparative Study of Z-Score and Min-Max Normalization for Rainfall Classification in Pekanbaru
Published 2024“…The findings demonstrate that applying normalization techniques effectively enhances classification performance compared to using unnormalized data. …”
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Kernel and multi-class classifiers for multi-floor wlan localisation
Published 2016“…The multi-class classification strategy is used to ensure quick estimation of the multi-class NN algorithms. …”
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8
Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm
Published 2018“…We introduced two new approaches to normalization techniques to enhance the K-Means algorithms. This is to remedy the problem of using the existing Min-Max (MM) and Decimal Scaling (DS) techniques, which have overflow weakness. …”
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9
An Educational Tool Aimed at Learning Metaheuristics
Published 2020“…Implemented with Java, this tool provides a friendly GUI for setting the parameters and display the result from where the learner can see how the selected algorithm converges for a particular problem solution. …”
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…The method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
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CNN architectures for road surface wetness classification from acoustic signals
“…Although machine learning algorithms such as recurrent neural networks (RNN), support vector machines (SVM), artificial neural networks (ANN) and convolutional neural networks (CNN) have been studied for road surface wetness classification, the improvement of classification performances are still widely being investigated whilst keeping network and computational complexity low. …”
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A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment
Published 2013“…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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Social spider optimisation algorithm for dimension reduction of electroencephalogram signals in human emotion recognition
Published 2018“…Whereby, the max accuracy obtained is 66.66% and 70.83%, the mean accuracy obtained is 55.51±7.17 and 60.97±8.38 for 3-level of valence emotions and 3-level of arousal emotions classification respectively.…”
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Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
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16
Brain Machine Interface Controlled Robot Chair
Published 2010“…Classification of the four hand motor imagery signals is presented using static and dynamic neural networks. …”
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Classification of compressive strength grades for lightweight aggregate concrete with palm oil fuel ash (POFA) using k-Nearest Neighbour (k-NN)
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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Automated plaque classification using computed tomography angiography and Gabor transformations
Published 2019“…Herein, we describe an automated algorithm to classify plaque as either normal, calcified, or non-calcified using 2646 CTA images acquired from 73 patients. …”
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Dense-cluster based voting approach for license plate identification
Published 2018“…This paper presents a new method called Dense Cluster based Voting (DCV) for identifying an input license plate image as normal or taxi such that suitable recognition algorithms can be used to achieve better recognition rate. …”
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