Search Results - (( java implementation learning algorithm ) OR ( pre implementation models algorithm ))
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1
Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions
Published 2017“…The project has also implemented the optimization process onto the proposed ANFIS model through the hybrid of Genetic Algorithm on the fuzzy membership function of the ANFIS model. …”
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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
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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4
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
Simulation model algorithm for pre-hospital emergency care (PHEC) volunteers in Indonesia
Published 2018“…The results reveals that simulation model using algorithm influences the improvement of traffic volunteers’ emergency management capabilities with p-value of < 0.05 and mean score difference of 34.5%, and the model is highly effective to be implemented to improve the capability of traffic assistant volunteers to manage trauma emergency with the mean score difference of 11.5%. …”
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7
Car dealership web application
Published 2022“…Tree SHAP, which was implemented by third-party SHAP Python library, were used in model monitoring and made the models interpretable. …”
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Final Year Project / Dissertation / Thesis -
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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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9
Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems
Published 2014“…A data parallel algorithm (DPA-EHD) is designed and implemented for the EHD equations. …”
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10
Rainfall prediction system using Artificial Neural Network (ANN) / Izzat Izzuddin Zulkarnain
Published 2024“…The methodology employed a systematic approach, including data collection, pre-processing, prototype architecture design, algorithm implementation, and evaluation. …”
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11
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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12
High Rise Building Evacuation Route Model Using DIJKSTRA'S Algorithm
Published 2015“…The information then is used to generate a directed graph in order to obtain the shortest path results through the implementation of shortest path algorithm. The main algorithms involve is Dijkstra’s algorithm and then an Ant Colony Optimization algorithm is used as hybrid versions of Dijkstra’s algorithm. …”
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13
Hand blood vessels pattern recognition
Published 2023“…The results showed that the proposed model achieved an 83.56% Dice Coefficient and 71.76% Jaccard Index, outperforming four handcrafted techniques tested and other pre-trained models. …”
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Final Year Project / Dissertation / Thesis -
14
Cohesive token passing algorithm utilizing software agents
Published 2010“…Approach: The implementation of Token Ring in MANET can be correlated to its complementary implementation in IP networks. …”
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Article -
15
The Design of Pre-Processing Multidimensional Data Based on Component Analysis
Published 2011“…RapidMiner is used for data pre-processing using FastICA algorithm. Kernel K-mean is used to cluster the pre-processed data and Expectation Maximization (EM) is used to model. …”
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16
Development of fault detection, diagnosis and control system identification using multivariate statistical process control (MSPC)
Published 2006“…Results showed that the developed FDD algorithm successfully detect and diagnosed the pre-designed faults. …”
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Monograph -
17
REAL AND SIMULATED MASKED FACE RECOGNITION WITH A PRE-TRAINED MODEL
Published 2023“…This change has encouraged the use of collaboration to resolve the related issues, which has resulted in the development of algorithms for face occlusion, collection of data on masked and unmasked faces and improvement of pre-trained models. …”
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18
Enhancement of parallel thinning algorithm for handwritten characters using neural network
Published 2005“…Thus, this project presents a framework for the implementation of a multilayer perceptron neural network with backpropagation algorithm, in the Parker thinning algorithm in order to produce a fast fully parallel thinning algorithm. …”
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19
Object detection in aerial images using Convolutional Neural Network (CNN) / Wan Nur Alya Athirah Wan Roshdee
Published 2024“…The model's performance depends on the task, dataset, architecture, and implementation. …”
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20
M-Factors Fuzzy Time Series for Forecasting Moving Holiday Electricity Load Demand in Malaysia (S/O 14589)
“…The modified algorithm, Weighted Subsethood Segmented Fuzzy Time Series (WeSuSFTS) consists of four main phases; data pre-processing, model development, model implementation and model evaluation. …”
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