Search Results - (( java implementation learning algorithm ) OR ( knowledge identification model algorithm ))
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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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Identification model for hearing loss symptoms using machine learning techniques
Published 2014“…The model is implemented using both unsupervised and supervised machine learning techniques in the form of Frequent Pattern Growth (FP-Growth) algorithm as feature transformation method and multivariate Bernoulli naïve Bayes classification model as the classifier. …”
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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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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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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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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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Fuzzy modelling using firefly algorithm for phishing detection
Published 2019“…A fuzzy system is a rule-based system that uses human experts’ knowledge to make a particular decision, while fuzzy modeling refers to the identification process of the fuzzy parameters. …”
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An artificial immune system model as talent performance predictor / Siti ‘Aisyah Sa’dan, Hamidah Jantan and Mohd Hanapi Abdul Latif
Published 2016“…The objective of this study is to propose a prediction model based on bio-inspired algorithm for talent knowledge discovery through some experiments. …”
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Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning
Published 2016“…The combination of gist, MTH and SIFT features increased the performance of image identification and showed 49% accuracy. Moreover, instead of concatenating feature vectors together and send to classifier, sparse coding and dictionary learning methods are used and instead of considering all features as one view (visual feature), K-SVD algorithm that is one of the famous algorithms for sparse representation is optimized and developed to multi-view model.The experimental results prove that the proposed methods has improved accuracy by 53.77% compared to concatenating features and classic K-SVD dictionary learning model as well.…”
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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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Fuzzy modelling for reboiler system
Published 2002“…Fuzzy system's ability of providing both heuristic knowledge with quantitative and accurate representation has been exploited for identification of nonlinear and complex system. …”
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Online system identification development based on recursive weighted least square neural networks of nonlinear hammerstein and wiener models.
Published 2022“…But this method has some drawbacks, among which is difficult for complex systems, sometimes is untraceable for nonlinear behavior that almost all systems have in the real world, and requires much knowledge. Another method is system identification which is also called experimental modeling. …”
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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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Talkout : Protecting mental health application with a lightweight message encryption
Published 2022“…The investigation of lightweight message encryption algorithms is conducted with systematic quantitative literature and experiment implementation in Java and Android running environment. …”
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Methods for identification of the opportunistic gut mycobiome from colorectal adenocarcinoma biopsy tissues
Published 2024“…•Application of machine learning algorithms to the identification of potential mycobiome biomarkers for non-invasive colorectal cancer screening. …”
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An analysis of text mining factors enhancing the identification of relevant studies
Published 2023“…Subsequently, we propose an agent based-text mining model that facilitate the identification of relevant studies in big databases. …”
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Parametric modelling of a TRMS using dynamic spread factor particle swarm optimisation
Published 2009“…Results in both time and frequency domains portray a very good parametric model that mimic well the behavior of a TRMS. Validation tests clearly show the effectiveness of the algorithm considered in this work. …”
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Proceeding Paper
