Search Results - (( knowledge visualization implementation algorithm ) OR ( java learning selection algorithm ))
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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
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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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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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4
High performance visualization of human tumor growth software
Published 2008“…The result of finite difference approximation (explicit, Crank-Nicolson and fully implicit methods) will be presented graphically. The implementation of parallel algorithm based on parallel computing system is used to visualize the growth of human tumour. …”
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5
Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Genetic algorithm GA had been adopted to perform features selection method; however, this method could not deliver an acceptable detection rate, lower accuracy, and higher false alarm rates. …”
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6
Thalassaemia detection using CBR Algorithm via mobile device
Published 2011“…Moreover,this application will be using the programming language Visual Basic. Net applied in Visual Studio 2008.The methodology has chosen is rapid application development (RAD) where this method is the archive with apparel search requirement. …”
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Undergraduates Project Papers -
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Thalassaemia detection using CBR Algorithm via mobile device
Published 2011“…Moreover,this application will be using the programming language Visual Basic. Net applied in Visual Studio 2008.The methodology has chosen is rapid application development (RAD) where this method is the archive with apparel search requirement. …”
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Ciphercrypt-an Encryption System / Nor Hidayah Ngah
Published 2004“…This system is implemented on a Windows platform with Visual Basic as a programming language and 3-DES as a main encryption algorithm. …”
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9
Fuzzy logic controller for an automatic car gearbox shifting
Published 2009“…The Fuzzy Logic components that were implemented included the fuzzification, knowledge base, inference engines and defuzzification. …”
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Kernerlized Correlation Filters Parameters Optimization For Enhanced Visual Tracking
Published 2017“…Until now, there are still no perfect algorithm to track the target flawlessly. In order to improve the performance, the main idea proposed is implementing optimization technique on the selected parameters and obtain a better performance. …”
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Monograph -
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Sentiment analysis of customer review for Tina Arena Beauty
Published 2025“…Future work may involve expanding the dataset, integrating real-time feedback systems, and evaluating advanced algorithms to improve classification performance further. …”
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Multi-modality ontology semantic image retrieval with user interaction model / Mohd Suffian Sulaiman
Published 2020“…This semantic technology is chosen due to the ability to mine, interpret and organise the knowledge. Ontology can be seen as a knowledge base that can be used to improve the image retrieval process with the aim of reducing the semantic gap between visual features and high-level semantics. …”
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Measuring Enterprise Architecture / Siti Fatimah Azzahra Ibrahim
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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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15
P300 detection of brain signals using a combination of wavelet transform techniques
Published 2012“…This research is proving the power of combination of discrete and continuous wavelet transform for achieving high accuracy in single trial detection and visualization of P300. Meanwhile the new approaches in channels selection methods help the algorithms for convenient online usage.…”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications
Published 2025“…The outcome of this study will add to the body of knowledge the most important and recent proposed solutions to mitigate SQL injection attack, in particular those based on machine learning algorithm…”
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Use of hybrid classification algorithm for land use and land cover analysis in data scarce environment
Published 2013“…In this study, vegetation indices, tasseled cap transformation, hybrid classification as a combination of k-means and support vector machine algorithms,and post-classification comparison were respectively implemented to detect and assess LULC in Halabja. …”
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18
Review on computational strategies for bi-layered metal powder compaction
Published 2024“…A scrutinize part is the implementation of algorithm to describe powder behavior under double loading as well as to relate with other mechanical variables that eventually require expertise on computational plasticity knowledges involving horizontal contacts. …”
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EEG-Based Person Authentication Modelling Using Incremental Fuzzy-Rough Nearest Neighbour Technique
Published 2016“…Fuzzy-Rough Nearest Neighbours (FRNN) technique is an outstanding technique to model uncertainty under an imperfect data condition. The current implementation of FRNN technique is not designed for incremental learning problem because there is no update function to incrementally reshape and reform the existing knowledge granules. …”
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