Search Results - (( java implementation learning algorithm ) OR ( program enhancing learning algorithm ))
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1
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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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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4
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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5
Enhancing programming language learning with 3D game-based programming for MSU students: codadventure / Abdullah Adib Aditia Wirawan and Nur Suhana Mohd Redzo
Published 2024“…This study focuses on innovative approaches to enhance the learning experiences of programming languages, focusing on developing 3D game-based programming for students at Management & Science University (MSU). …”
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6
Effectiveness of algorithm visualisation in studying complex algorithms: a case study using TRAKLA Ravie / Chandren Muniyandi, Ali Maroosi
Published 2015“…TRAKLA2 is a visualisation tool used to enhance the process of learning algorithm construction and optimization. …”
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Particle swarm optimization for neural network learning enhancement
Published 2006“…In this study, the latest optimization algorithm, Particle Swarm Optimization (PSO) is chosen and applied in feedforward neural network to enhance the learning process in terms of convergence rate and classification accuracy. …”
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8
Case Slicing Technique for Feature Selection
Published 2004“…The classification accuracy obtained from the CST method is compared to other selected classification methods such as Value Difference Metric (VDM), Pre-Category Feature Importance (PCF), Cross-Category Feature Importance (CCF), Instance-Based Algorithm (IB4), Decision Tree Algorithms such as Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5), Rough Set methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) and Neural Network methods such as the Multilayer method.…”
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9
Hybrid Ant Colony Optimization For Two Satisfiability Programming In Hopfield Neural Network
Published 2019“…The newly proposed metaheuristic algorithm was enhanced ant colony optimization (ACO) algorithm.…”
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10
Enhancing understanding of programming concepts through physical games
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Enhancing problem-solving skills of novice programmers in an introductory programming course
Published 2023Article -
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Differential evolution for neural networks learning enhancement
Published 2008“…Three programs have developed; Differential Evolution Neural Network (DENN), Genetic Algorithm Neural Network (GANN) and Particle Swarm Optimization with Neural Network (PSONN) to probe the impact of these methods on ANN learning using various datasets. …”
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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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15
Assessment of using EZ-Prog: an easy color schematic model for programming problem solving
Published 2020“…This demonstrates the EZ-Prog technique used in learning programming problem-solving learning enhances student problem-solving skills. …”
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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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17
Learning analytic framework for students’ academic performance and critical learning pathways
Published 2024“…By providing a holistic perspective of student performance and course interactions, the proposed learning analytics framework holds great promise for educational institutions seeking data-driven strategies to enhance student outcomes and optimize learning experiences.…”
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Implementation of Health Monitoring System for Patients using Machine Learning Algorithms
Published 2024“…It did this by using a fuzzy logic classifier for illness prediction and a random forest for feature selection. Additionally, to enhance overall equipment effectiveness (OEE), lower electricity costs, and decrease unplanned downtime in manufacturing settings, we created a real-time system leveraging smart systems and machine learning. …”
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Machine learning predictions of stock market pattern using Econophysics approach
Published 2025“…In conclusion, the study of Econophysics principles with Python programming and machine learning algorithms has indicates that the predictive framework is reliable and effective in capturing stock price fluctuations, enhancing decision-making for investors based on data-driven insights.…”
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AI recommendation penetration testing tool for cross-site scripting: support vector machine algorithm
Published 2025“…The SVM algorithm, a supervised learning model, plays a crucial role in improving the efficiency of tool selection, ultimately enhancing the speed and adaptability of vulnerability detection processes. …”
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