Search Results - (( java implementation learning algorithm ) OR ( using training using 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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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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4
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 improved artificial bee colony algorithm for training multilayer perceptron in time series prediction
Published 2014“…Furthermore, here these algorithms used to train the MLP on two tasks; the seismic event's prediction and Boolean function classification. …”
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8
Evaluation of MLP-ANN Training Algorithms for Modeling Soil Pore-Water Pressure Responses to Rainfall
Published 2013“…It was found that all the training algorithms could be used in the prediction of pore-water pressures. …”
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9
River Suspended Sediment Prediction Using Various Multilayer Perceptron Neural Network Training Algorithms—A Case Study in Malaysia
Published 2012“…It was concluded that both training algorithms SCG and LM could be recommended for suspended sediment prediction using MLP networks. …”
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10
Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…Based on the results, the EP algorithm achieved a higher training rate and simple structure compared with the rest of the algorithms. …”
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Sentiment classification for malay newspaper using clonal selection algorithm / Nur Fitri Nabila Mohamad Nasir
Published 2013“…Therefore, 80% from 1000 sentences will use for training and 20% from 1000 sentences use for testing. …”
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12
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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Backpropagation neural network training algorithm analysis / Shahrul Azmi Rosli
Published 2010“…This paper presents the analysis of Backpropagation Neural Network Training Algorithms in Artificial Neural Network (ANN) using MATLAB and demonstrates the analysis of training algorithms using the dataset of concrete compressive strength.…”
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14
Dynamic training rate for backpropagation learning algorithm
Published 2013“…In this paper, we created a dynamic function training rate for the Back propagation learning algorithm to avoid the local minimum and to speed up training.The Back propagation with dynamic training rate (BPDR) algorithm uses the sigmoid function.The 2-dimensional XOR problem and iris data were used as benchmarks to test the effects of the dynamic training rate formulated in this paper.The results of these experiments demonstrate that the BPDR algorithm is advantageous with regards to both generalization performance and training speed. …”
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Neural Network Training Using Hybrid Particle-move Artificial Bee Colony Algorithm for Pattern Classification
Published 2017“…By optimizing the training of the neural networks using optimal weight set, better results can be obtained by the neural networks. …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…Based on the results, the EP algorithm achieved a higher training rate and simple structure compared with the rest of the algorithms. …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…Based on the results, the EP algorithm achieved a higher training rate and simple structure compared with the rest of the algorithms. …”
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18
Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…Based on the results, the EP algorithm achieved a higher training rate and simple structure compared with the rest of the algorithms. …”
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19
Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…Based on the results, the EP algorithm achieved a higher training rate and simple structure compared with the rest of the algorithms. …”
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20
Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…Based on the results, the EP algorithm achieved a higher training rate and simple structure compared with the rest of the algorithms. …”
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