Search Results - (( java implementation learning algorithm ) OR ( programming gain efficient 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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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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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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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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Simultaneous Network Reconfiguration and DG Sizing Using Evolutionary Programming and Genetic Algorithm to Minimize Power Losses
Published 2014“…This paper presents an effective method based on Evolutionary Programming (EP) and Genetic Algorithm (GA) to identify the switching operation plan for feeder reconfiguration and distributed generation size simultaneously. …”
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Coordination of PSS and PID controller for power system stability enhancement - overview
Published 2023“…This paper broadly reviews the optimization methods and algorithms such as Conventional methods, Soft Computing, Genetic Algorithm (GA), Evolutionary Programming (EP), Differential Evolution (DE) and Swarm Intelligence methods were available for tuning the PID gains and PSS parameters successfully. …”
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Long-term rain attenuation probability and site diversity gain prediction formulas
Published 2007“…It includes the designing of algorithm flow which incorporated into MATLAB programming software. …”
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An analysis on the applicability of meta-heuristic searching techniques for automated test data generation in automatic programming assessment
Published 2019“…Automatic Programming Assessment (APA) has been gaining lots of attention among researchers mainly to support automated grading and marking of students’ programming assignments or exercises systematically. …”
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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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A framework for GPU-accelerated AES-XTS encryption in mobile devices
Published 2011“…Recently, GPUs have presented higher performance for parallel programming than conventional CPUs while they continue gaining reduced cost. …”
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An efficacious multi-objective fuzzy linear programming approach for optimal power flow considering distributed generation
Published 2016“…An efficacious multi-objective fuzzy linear programming optimization (MFLP) algorithm is proposed to solve the aforementioned problem with and without considering the distributed generation (DG) effect. …”
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Reverse logistics network optimizing by genetic algorithm: a case study of automotive wiring harnesses
Published 2014“…Thus, an evolutionary algorithm based genetic algorithm (GA) is applied as a solution methodology to solve mixed integer linear programming model and find the optimum solution. …”
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Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform
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Security analysis of data transmission in an IoT based platform for telemedicine
Published 2021“…Using less power, the proposed architecture is implemented based on python programming language, thereby improving time and power requirements compared to the traditional algorithm. …”
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New reflector shaping methods for dual-reflector antenna
Published 2022“…First, the equivalent parabola and circle equation is implemented in the reflector shaping algorithms. Second, a Matrix Laboratory (MATLAB) program is developed in order to obtain the main and sub reflector shapes. …”
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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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