Search Results - (( java implementation learning algorithm ) OR ( parameters problems faces 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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Exploring dynamic self-adaptive populations in differential evolution
Published 2006“…In addition to reducing the number of parameters used in DE, the proposed algorithm actually outperformed the conventional DE algorithm for one of the test problems. …”
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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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Tackling the berth allocation problem via harmony search algorithm
Published 2024“…Many metaheuristic algorithms have been suggested to tackle this problem, and yet, most of these algorithms have some drawbacks such as they have a weak ability to explore the solution space (they struggle escaping from local minima) and they face the difficulties to operate on different datasets. …”
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Hybrid evolutionary optimization algorithms: A case study in manufacturing industry
Published 2014“…Such complex problems of vagueness and uncertainty can be handled by the hybrid evolutionary intelligence algorithms. …”
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Neural Network Multi Layer Perceptron Modeling For Surface Quality Prediction in Laser Machining
Published 2009“…In this research, we investigated a problem solving scenario for a metal cutting industry which faces some problems in determining the end product quality of Manganese Molybdenum (Mn-Mo) pressure vessel plates. …”
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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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Development Of An Algorithm To Reduce The Topographical Effects In Reflected Radiance
Published 2020“…Many researchers have tried to reduce the effect of topography in the past with success; however, most of these methods are complicated and require many parameters. To address this problem, we developed algorithms that quantify, reduce, and induce topographical effects in satellite images by exploring the relationship between direct and diffuse solar irradiance. …”
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Modified least trimmed squares method for face recognition / Nur Azimah Abdul Rahim
Published 2018“…For most face recognition algorithms, partial occlusions affect the performance of the algorithm. …”
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Convolutional neural networks with fused layers applied to face recognition
Published 2015“…In this paper, we propose an e®ective convolutional neural network (CNN) model to the problem of face recognition. The proposed CNN architecture applies fused convolution/ subsampling layers that result in a simpler model with fewer network parameters; that is, a smaller number of neurons, trainable parameters, and connections. …”
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An improved back propagation leaning algorithm using second order methods with gain parameter
Published 2018“…It has successfully been implemented in various practical problems. However, the algorithm still faces some drawbacks such as getting easily stuck at local minima and needs longer time to converge on an acceptable solution. …”
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Multi-step time series prediction using recurrent kernel online sequential extreme learning machine / Liu Zongying
Published 2019“…Recent years, Machine correlation and potential non stationary of the data can be automatically analyzed. However, the problems with traditional offline and online learning algorithms in machine learning algorithms are usually faced with parameter dependency, concept drift handling problem, connectionless of neural net and unfixed reservoir. …”
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Human face detection from color images: preliminary result
Published 2004“…Such problems are quite challenging because the faces are non-rigid and have a high degree of variability in size, shape, color and texture. …”
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