Search Results - (( java implementation learning algorithm ) OR ( learning process study algorithm ))
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A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment
Published 2013“…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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2
Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…This work employed the use of machine learning approach. Four conventional classification algorithms: naïve bayes (NB), support vector machines (SVM), nearest neighbor (k-NN), and decision trees (J48) classifiers are implemented in identifying and categorizing tweet data of three political figures in Malaysia: Dato Seri Anwar, Dato Hadi Awang, and Lim Guang Eng, as either positive, negative, or neutral perceptions. …”
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3
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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4
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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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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6
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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7
Supervised deep learning algorithms for process fault detection and diagnosis under different temporal subsequence length of process data
Published 2025“…Deep learning algorithms were widely used among all the data-driven algorithms. …”
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Effect of chaos noise on the learning ability of back propagation algorithm in feed forward neural network
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Working Paper -
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Integration of image processing algorithm and deep learning approaches to monitor ginger plant
Published 2024“…This study aims to integrate image processing and deep learning algorithms to monitor the growth of ginger plants. …”
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Final Year Project / Dissertation / Thesis -
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Elucidating the effect of process parameters on the production of hydrogen-rich syngas by biomass and coal Co-gasification techniques: A multi-criteria modeling approach
Published 2023“…Biomass; Coal; Complex networks; Errors; Forecasting; Gasification; Hydrogen production; Learning algorithms; Mean square error; Neural networks; Regression analysis; Sensitivity analysis; Support vector machines; Co-gasification; Gaussian process regression; Hydrogen-rich syngas; Machine learning algorithms; Machine-learning; Neural-networks; Process parameters; Regression model; Support vectors machine; Syn gas; Synthesis gas; coal; hydrogen; synfuel; biomass; chemical reaction; detection method; hydrogen; machine learning; multicriteria analysis; algorithm; Article; artificial neural network; biomass; controlled study; gasification; Gaussian processing regression; linear regression analysis; machine learning; mean absolute error; mean square error; parameters; prediction; root mean square error; sensitivity analysis; support vector machine; temperature; Bayes theorem; biomass; Bayes Theorem; Biomass; Coal; Hydrogen; Temperature…”
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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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Performance comparison of different machine learning algorithms on a time-series of covid-19 data: A case study for Saudi Arabia
Published 2021“…In this study we have applied several machine learning algorithms to analyse time-series data related to COVID-19 in Saudi Arabia. …”
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Performance comparison of different machine learning algorithms on a time-series of covid-19 data: A case study for Saudi Arabia
Published 2021“…In this study we have applied several machine learning algorithms to analyse time-series data related to COVID-19 in Saudi Arabia. …”
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Enhancement processing time and accuracy training via significant parameters in the batch BP algorithm
Published 2020“…The average accuracy training is 0.9909 and average processing time improved of dynamic algorithm is 430 times faster than the BBP algorithm. …”
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15
Integration of image processing algorithm and deep learning approaches to monitor ginger plant
Published 2024“…This study aims to integrate image processing and deep learning algorithms to monitor the growth of ginger plants. …”
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Final Year Project / Dissertation / Thesis -
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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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A Reference Based Surface Defect Segmentation Algorithm For Automatic Optical Inspection System
Published 2020“…This study aims to develop an algorithm for the AOI system to segment and detect surface defects, requiring low processing power and a small number of learning dataset with labelling error resistance. …”
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19
A comparative analysis of machine learning algorithms for diabetes prediction
Published 2024“…The study contributes insights into the importance of pre-processing and feature selection in improving algorithm performance. …”
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Evaluating the performance of machine learning techniques in the classification of Wisconsin Breast Cancer
Published 2018“…Therefore, the automation of this process is required to recognize tumors. Numerous research works have tried to apply the algorithms of machine learning for classifying breast cancer and it was proven by many researchers that machine learning algorithms act preferable in the diagnosing process. …”
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