Search Results - (( java implementation learning algorithm ) OR ( programming scale selection 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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Sizing optimization of large-scale grid connected photovoltaic system using dolphin echolocation algorithm / Muhammad Zakyizzuddin Rosselan
Published 2018“…Besides DEA, Evolutionary Programming (EP), Firefly Algorithm (FA) and Cuckoo Search Algorithm (CS) were also incorporated in the sizing algorithm for performance comparison. …”
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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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A combined filter line search and trust region method for nonlinear programming
Published 2006“…Computational results on selected large scale CUTE problems on the prototype code fiILS are very encouraging and numerical performance with LOQO and SNOPT show that the algorithm is efficient and reliable.…”
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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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CSC099: Foundation Computing II / Centre of Foundation Studies
Published 2022“…This course introduces basic computer programming algorithm, problem solving, structured programming language, selection structure, repetition structure, function and array. …”
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An Efficient Genetic Algorithm for Large Scale Vehicle Routing Problem Subject to Precedence Constraints
Published 2015“…In order to obtain feasible solution which does not violate precedence constraints, a route repair based topological sort technique is used and integrated in the genetic algorithm procedure. In this paper, a new algorithm is developed and the performances as well as the quality of the solution were evaluated against large scale test problems. …”
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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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Image classification using two dimensional wavelet coefficients with parallel computing
Published 2020“…This research algorithm demonstrated a very promising result with Support Vector Machines, this algorithm produces a 90% of accuracies whereas the decision tree algorithm gets 100% accuracies. …”
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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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Efficient genetic partitioning-around-medoid algorithm for clustering
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Smart energy meter with adaptive communication data transfer algorithm for electrical energy monitoring
Published 2021“…The prototype is constructed through software and hardware development and has been programmed using Arduino IDE software. An algorithm for selecting communication system is developed by comparing Received Signal Strength Indicator (RSSI) of Wi-Fi and GSM with the priority given to Wi-Fi, followed by GSM and RF. …”
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Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform
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Development of priority oriented scheduling method to increase the efficiency and reliability for automotive job
Published 2012“…Secondly, the jobs should be arranged based on three criteria which are priority, time action and time stamp. This sorting algorithm is programmed via MATLAB distributed computing server (DCS) software. …”
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A cluster-based hybrid replica control protocol for high availability in data grid
Published 2019“…Another proposed algorithm is replica placement algorithm which selects and places only one replica in each cluster. …”
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Comparative Analysis Using Bayesian Approach To Neural Network Of Translational Initiation Sites In Alternative Polymorphic Contex
Published 2012“…The objectives of this paper are to develop useful algorithms and to build a new classification model for the case study.The first approach of neural network includes training on algorithms of Resilient Backpropagation,Scaled Conjugate Gradient Backpropagation and Levenberg-Marquardt.The outputs are used in comparison with Bayesian Neural Network for efficiency comparison.The results showed that Resilient Backpropagation have the consistency in all measurement but performs less in accuracy.In second approach,the Bayesian Classifier_01 outperforms the Resilient Backpropagation by successfully increasing the overall prediction accuracy by 16.0%.The Bayesian Classifier_02 is built to improve the accuracy by adding new features of chemical properties as selected by the Information Gain Ratio method,and increasing the length of the window sequence to 201.The result shows that the built model successfully increases the accuracy by 96.0%.In comparison,the Bayesian model outperforms Tikole and Sankararamakrishnan (2008) by increasing the sensitivity by 10% and specificity by 26%. …”
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