Search Results - (( java implementation learning algorithm ) OR ( parameter extraction machine 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
Assessing the efficacy of machine learning algorithms for syncope classification: A systematic review
Published 2024“…Machine learning improves syncope diagnosis compared to traditional scoring, requiring fewer parameters. …”
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3
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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5
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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6
Modeling, Testing and Experimental Validation of Laser Machining Micro Quality Response by Artificial Neural Network
Published 2009“…Therefore, prediction of laser machining cut quality, namely surface roughness was carried out using machine learning techniques based on Quick Back Propagation Algorithm using ANN. …”
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7
Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images
Published 2024“…In the third classification algorithm, hybrid features are extracted using AlexNet and VGG-16 through a transfer learning approach where parameter manipulation is implemented to simplify the network. …”
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8
Machine learning methods for herschel-bulkley fluids in annulus: Pressure drop predictions and algorithm performance evaluation
Published 2020“…The impact of each input parameter affecting the pressure drop is quantified using the RF algorithm. …”
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Design of efficient blue phosphorescent bottom emitting light emitting diodes by machine learning approach
Published 2018“…This study demonstrates the applicability of machine learning algorithm in extracting underlying complex correlations in blue PhOLEDs.…”
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Study of machine learning in computer vision using Raspberry Pi
Published 2024text::Final Year Project -
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Application of image processing and adaptive neuro-fuzzy system for estimation of the metallurgical parameters of a flotation process
Published 2016“…Furthermore, the metallurgical parameters of a laboratory flotation cell were successfully predicted from the extracted froth features. …”
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Enhancement Of Static Code Analysis Malware Detection Framework For Android Category-Based Application
Published 2021“…Too many features used, features extraction time consuming and the reliability of accuracy result by various machine learning algorithm are the main issues spotted in static analysis approach. …”
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14
Building detection using object-based Image analysis (OBIA) and machine learning (ML) algorithms / Hanani Mohd Shahar
Published 2020“…In order to obtain a good classification accuracy, the suitable segmentation parameters (scale, shape and compactness) and features selection have been determined and Machine learning (ML) algorithms, namely Support Vector Machine (SVM) and Decision Tree (DT) classifiers have been applied to categorized five different classes which are water, forest, green area, building, and road. …”
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A new model for iris data set classification based on linear support vector machine parameter's optimization
Published 2020“…In this study, we proposed a newly mode for classifying iris data set using SVM classifier and genetic algorithm to optimize c and gamma parameters of linear SVM, in addition principle components analysis (PCA) algorithm was use for features reduction.…”
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Prediction of Ground Surface Deformation Induced by Earthquake on Urban Area Using Machine Learning
Published 2023“…Four machine learning algorithms of Neural Network (NN), Random Forest (RF), k-Nearest Neighbors (kNN), and Gradient Boosting (GB) are applied. …”
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Sentiment Analysis of Sexual Harassment in Malaysia on Twitter Using Machine Learning Algorithms
Published 2023“…The transformed data is then modelled using machine learning algorithms such as Naïve Bayes classifier and Support Vector Machine to predict the overall sentiment of tweets, in which the finding depicted an overall positive sentiment surrounding the issue. …”
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An Arabic hadith text classification model using convolutional neural network and support vector machine / Mohd Irwan Mazlin
Published 2022“…Convolution Neural networks and support vector machines are two different algorithms applied to text classification. …”
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Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan
Published 2020“…In the modeling phase, amongst all DM algorithms, the applicability of machine learning, artificial intelligence and statistical data mining techniques were examined using Support Vector Machine (SVM), Artificial Neural Network (ANN) and Classification and Regression Tree (CART) to detect the hidden patterns in vibration data. …”
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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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