Search Results - (( java implementation learning algorithm ) OR ( knowledge integration modelling 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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2
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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Conference or Workshop Item -
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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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SURE-Autometrics algorithm for model selection in multiple equations
Published 2016“…This automatic model selection algorithm is better than non-algorithm procedure which requires knowledge and extra time. …”
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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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Algorithm-program visualization model : An intergrated software visualzation to support novices' programming comprehension
Published 2015“…Taking into account from those main issues, this study introduces the new model of integrated algorithm-program visualization (ALPROV) for developing program comprehension tool. …”
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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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9
Development of a modified adaptive protection scheme using machine learning technique for fault classification in renewable energy penetrated transmission line
Published 2020“…The hybrid Wavelet Multiresolution Analysis and Machine learning algorithm (WMRA-ML) is used to extracts the useful hidden knowledge from decomposed one-cycle fault transient signals (voltage & current) from four Matlab/Simulink CIGRE models. …”
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Eye Diagram Modeling Of High-Speed Channels Using Artificial Neural Networks With An Improved Adaptive Sampling Algorithm
Published 2019“…xxiii EYE DIAGRAM MODELING OF HIGH-SPEED CHANNELS USING ARTIFICIAL NEURAL NETWORKS WITH AN IMPROVED ADAPTIVE SAMPLING ALGORITHM ABSTRACT As data rates increase to the gigabit range and beyond, signal integrity (SI) analysis becomes increasingly difficult and time consuming process. …”
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Hyper-heuristic framework for sequential semi-supervised classification based on core clustering
Published 2020“…The genetic optimization is responsible for selecting the best parameters of the core model to minimize the error. This integration aims to handle the concept drift. …”
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Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things
Published 2022“…Existing literature relies on offline trained models or incremental learning models. The former suffers from partially or fully outdated knowledge after drift occurrence, and the latter suffers from the constraints of the pre-defined hyper-parameter of the model. …”
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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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Academic Exercise -
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Research on the construction of an efficient and lightweight online detection method for tiny surface defects through model compression and knowledge distillation
Published 2024“…Channel pruning and layer pruning are applied to the sparse model, and post-processing methods using knowledge distillation are used to effectively reduce the model size and forward inference time while maintaining model accuracy. …”
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Machine-learning-based adaptive distance protection relay to eliminate zone-3 protection under-reach problem on statcom-compensated transmission lines
Published 2020“…The BayesNet provides the best integrated MLADR fault classifier model better at a 5 % significance level than other deployed algorithms in the intelligent supervised learning model realization. …”
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A Mobile Application For Stock Price Prediction
Published 2021“…There are a few prediction algorithms being evaluated which were Long Short-Term Memory (LSTM), Holt Winter, AutoRegression Integrated Moving Average (ARIMA), Seasonal Auto-Regression Integrated Moving Average (SARIMA) and Prophet. …”
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Final Year Project / Dissertation / Thesis -
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A hybrid intelligent algorithm for solving the bilevel programming models
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Working Paper -
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Automatic clustering of gene ontology by genetic algorithm
Published 2006“…Abstract—Nowadays, Gene Ontology has been used widely by many researchers for biological data mining and information retrieval, integration of biological databases, finding genes, and incorporating knowledge in the Gene Ontology for gene clustering. …”
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Integrated applications of building information modeling in project cost management: a systematic review
Published 2023“…Also, BIM can be applied independently or integrated with other techniques. The integrated approaches for cost control include integration with genetic algorithms, Monte Carlo simulation, lean construction, integrated project delivery, neural network and value engineering. …”
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