Search Results - (( java implementation learning algorithm ) OR ( machine learning replication algorithm ))
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Exploration of machine learning forecasting methods in M4 competition / Muhammad Halim Hamdan and Shuzlina Abdul-Rahman
Published 2021“…Three machine learning techniques from M4 Competition were chosen to be compared in this research. …”
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2
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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3
Rockfall source identification using a hybrid Gaussian mixture-ensemble machine learning model and LiDAR data
Published 2019“…The availability of high-resolution laser scanning data and advanced machine learning algorithms has enabled an accurate potential rockfall source identification. …”
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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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7
Securing IoT networks using machine learning-resistant physical unclonable functions (PUFs) on edge devices
Published 2026“…The predictive performance of five machine learning algorithms, i.e., Support Vector Machines, Logistic Regression, Artificial Neural Networks with a Multilayer Perceptron, K-Nearest Neighbors, and Gradient Boosting, was analyzed, and the results showed an average accuracy of approximately 60%, demonstrating the strong resistance of the RO PUF to these attacks. …”
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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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Assessment of suitable hospital location using GIS and machine learning
Published 2022“…Third, an insight into the machine learning models utilized and how their predicted weights affect hospital site suitability mapping was provided. …”
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Efficient Malware Detection And Response Model Using Enhanced Parallel Deep Learning (EPDL-MDR)
Published 2026“…Upon converting PE files to images, the deep learning pixel-matching algorithm identifies obscured malware features. …”
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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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A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification
Published 2023“…Machine learning (ML) practices such as classification have played a very important role in classifying diseases in medical science. …”
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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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Allah’s wisdom in creating the universe as a source of inspiration in artificial intelligence
Published 2024“…As artificial intelligence (AI) continues to transform human capabilities, enabling machines to replicate cognitive functions and behaviours, the importance of balancing material pursuits with spiritual and ethical considerations becomes increasingly significant. …”
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15
HARC-New Hybrid Method with Hierarchical Attention Based Bidirectional Recurrent Neural Network with Dilated Convolutional Neural Network to Recognize Multilabel Emotions from Text
Published 2021“…On a variety of datasets, our proposed HARC algorithm solution outperformed traditional machine learning approaches as well as comparable deep learning models by a margin of 1%. …”
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Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform
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Development of a hybrid machine learning model for rockfall source and hazard assessment using laser scanning data and GIS
Published 2019“…This is based on highresolution Light Detection and Ranging (LiDAR) techniques both airborne and terrestrial (ALS and TLS). Different machine learning algorithms (Artificial Neural Network [ANN], K Nearest Neighbor [KNN] and Support Vector Machine [SVM]) were tested individually and with various ensemble models (bagging, voting, and boosting) to detect the probability of the landslide and rockfall occurrences. …”
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Enhancing teaching and learning through data-driven optimization of servicing code demand and lecturer allocation using WEKA analysis
Published 2025“…These re suggest that machine learning driven approaches can effectively support academic administrations in making informed staffing decisions, balancing full time and part time lecturer assignments, and optimizing cost structures without compromising teaching quality. …”
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Performance Prediction of Compulsory Subjects and Recommendation of Subject Options for China’s New College Entrance Examination
Published 2026“…The dataset was split 80/20 for training and testing. Four machine learning algorithms: Naïve Bayes (NB), Decision Tree (DT), Artificial Neural Networks (ANNs), and Support Vector Machines (SVMs) were evaluated using accuracy, precision, recall, F1 score, and Matthews Correlation Coefficient (MCC). …”
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A malware analysis and detection system for mobile devices / Ali Feizollah
Published 2017“…We then used feature selection algorithms and deep learning algorithms to build a detection model. …”
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