Search Results - (( java implementation learning algorithm ) OR ( layer perception study algorithm ))
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1
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
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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3
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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5
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
An application of artificial neural network on short term load forecasting using back propagation algorithm / Elia Erwani Hassan
Published 1998“…The Back Propagation Algorithm, which consists of the multi-layered perception model, makes possible to train the ANN training pattems. …”
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8
IoT Soil Moisture Monitoring and Irrigation System Development
Published 2020“…At the same time, with a self-sufficient and self-organized irrigation system based on the water-control algorithm. The developed system covered the three layers in IoT architecture: perception layer, network layer and application layer. …”
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Proceeding -
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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 -
10
Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform
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Conference or Workshop Item -
11
Forecasting The Growth of Manufacturing Industry in Malaysia Using Artificial Neural Network
Published 2006“…The effectiveness of ANN for predicting one criterion, Y form several predictors, X, is investigated. Comparative studies are examined between the result of the predictions from the ANN model trained with Multi-Layer Feed forward Perception, a Generalised Regressions Neural Network (GRNN) algorithm and the result obtained from traditional statistical approach.…”
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12
Application of artificial neural network in discriminating the agarwood oil quality using significant chemical compounds / Mohd Hezri Fazalul Rahiman … [et al.]
Published 2014“…Data Processing - ANN Application ( Data pre-processing using Z-score, ANN design structure/architecture - parameter optimisation, training and testing the algorithm) Result & Discussion: ANN parameter optimisation - final error for learning rate, momentum rate and hidden layer size ANN final design parameter - Nodes in input layer: 7, Nodes in hidden layer size: 2, Output layer size: 1, learning rate: 0.9, Momentum rate: 0.7, Error goal: 0.01, Epochs: 100 ANN prediction: high accuracy for training and testing prediction (refer to the figure in poster) Patent & List of contributions: 1. …”
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Book Section -
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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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14
Multivariate Time Series Forecasting Of Crude Palm Oil Price Using Machine Learning Techniques
Published 2017“…Experiments were conducted using multi-layer perception, support vector regression and Holt Winter exponential smoothing techniques.The results were assessed by using criteria of root mean square error (RMSE),means absolute error (MAE),means absolute percentage error (MAPE) and Direction of accuracy (DA).Among these three techniques, support vector regression(SVR) with Sequential minimal optimization (SMO) algorithm showed relatively better results compared to multi-layer perceptron and Holt Winters exponential smoothing method. …”
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Article -
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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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16
Artificial neural network modeling of grinding of ductile cast iron using water based sio2 nanocoolant
Published 2014“…An artificial neural network model is developed for predicting the surface roughness and MRR. Multi-layer perception and a batch back propagation algorithm are used. …”
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Cyber-Crime Detection: Experimental Techniques Comparison Analysis
Published 2023“…The objective of this research paper is to conduct experimental techniques comparison analysis for cyber-crime detection by reviewing all possible machine learning algorithms for automatic detection. The key focus of the study is on the use of eight classifiers models which are Logistic Regression (LR), Decision Tree (DT), K-nearest Neighbors (KNN), Support Vector Machine (SVM), Naive Bayes (NB), Random Forest (RF), eXtreme Gradient Boosting (XGBoost) and Multiple layer perception (MLP). …”
Conference Paper -
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Optimization of abrasive machining of ductile cast iron using water based SiO2 nanocoolant : a radial basis function
Published 2012“…Artificial neural network (ANN) model is developed for predicting the results of the surface roughness and MRR. Multi-Layer Perception (MLP) along with batch back propagation algorithm are used. …”
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Undergraduates Project Papers -
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