Search Results - (( java implementation learning algorithm ) OR ( making program learning 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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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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Dam haji game using A* search algorithm / Siti Farah Najwa Mukhlis
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Assessment of using EZ-Prog: an easy color schematic model for programming problem solving
Published 2020“…The implications of this study indicate that EZ-Prog can be used in learning and teaching algorithms, especially programming problems. …”
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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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Impact learning: A learning method from feature's impact and competition
Published 2023“…Machine learning algorithms build a model from sample data, called training data, to make predictions or judgments without being explicitly programmed to do so. …”
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Impact learning : A learning method from feature’s impact and competition
Published 2023“…Machine learning algorithms build a model from sample data, called training data, to make predictions or judgments without being explicitly programmed to do so. …”
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Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation
Published 2023Conference paper -
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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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Impact learning: A learning method from feature’s impact and competition
Published 2023“…Machine learning algorithms build a model from sample data, called training data, to make predictions or judgments without being explicitly programmed to do so. …”
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Development of an intelligent information system for financial analysis depend on supervised machine learning algorithms
Published 2022“…This type of algorithm can aid financial institutions in making grant selections for their clients. …”
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Modeling a problem solving approach through computational thinking for teaching programming / Zebel Al Tareq
Published 2021“…Different teaching approaches for programming are widespread but what is essential for students is being able to computationally formulate an algorithmic solution at first and then transfer to code. …”
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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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Recognition of isolated elements picture using backpropagation neural network / Melati Sabtu
Published 2005“…There are three main programs work together. The programs are back-propagation neural network program, training and performance program and recognition program. …”
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Deep Reinforcement Learning For Control
Published 2021“…In essence, the method is to use a reward-based learning environment to watch how the agent makes decisions. …”
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Artificial Intelligence (AI) in the art and design industry / Fahmi Samsudin
Published 2023“…It encompasses different types, such as rule-based AI using if-then statements for decision-making, machine learning which employs algorithms to analyze and learn from data, and deep learning utilizing artificial neural networks to learn from extensive datasets. …”
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Teaching and learning via chatbots with immersive and machine learning capabilities
Published 2019“…Each of these chatbots focuses on different programming concepts or constructs. These chatbots support learning of Java via problem-solving steps through “learning by doing”. …”
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