Search Results - (( based verification learning algorithm ) OR ( code classification mining algorithm ))
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Evaluations of oil palm fresh fruit bunches maturity degree using multiband spectrometer
Published 2017“…Furthermore, the Lazy-IBK algorithm have been validated to produce the best classifier model, with the machine learning algorithm performance of 65.26%, recall of 65.3%, and 65.4% F-measured as compared to other evaluated machine learning classifier algorithms proposed within the WEKA data mining algorithm. …”
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Thesis -
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Comparative analysis for topic classification in juz Al-Baqarah
Published 2018“…The SVM performance is then compared against other classification algorithms such as Naive Bayes, J48 Decision Tree and K-Nearest Neighbours. …”
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Classification of metamorphic virus using n-grams signatures
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Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool
Published 2018“…No EEG studies in Malaysia has been done on school children to study their emotional behaviour while learning. Classification and prediction are the functions provided by the data mining techniques that suit in EEG signal processing. …”
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An efficient technique for human verification using finger stripes geometry
Published 2007“…Finger stripe geometry is a new biometric type in verification process. This finger stripe based verification consists of two main attributes, feature extraction by image processing and feature learning by ANN (Artificial Neural Network). …”
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Person Verification Based on Multimodal Biometric Recognition
Published 2022“…The algorithm is extensively evaluated on UCI Machine Learning Repository Database datasets, including one real dataset with state-of-the-art approaches. …”
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Efficient ML technique in blockchain-based solution in carbon credit for mitigating greenwashing
Published 2025“…This literature review explores the integration of blockchain technology and machine learning (ML) to enhance verification processes and reduce fraudulent practices in forest carbon credits. …”
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Development of optimized damage prediction method for health monitoring of ultra high performance fiber-reinforced concrete communication tower
Published 2018“…The results are used to develop the hybrid learning algorithm based on the AdaBoost, Bagging, and RUSBoost methods to predict the damage in the tower based on dynamic frequency domain. …”
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An intelligent framework for modelling and active vibration control of flexible structures
Published 2004“…The simulation algorithm and interactive environment thus developed and validated form suitable test and verification platforms for the development of AVC strategies for flexible structures as well as for learning and research purposes.…”
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An enhanced android botnet detection approach using feature refinement
Published 2019“…The experimental and statistical tests show that 97.28% accuracy achieved by Random Forest machine classifier, it performs well as compared to other classification algorithms. Based on the test results, various open research issues which need to be addressed in future studies are highlighted.…”
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Raspberry Pi-Based Finger Vein Recognition System Using PCANet
Published 2018“…For classification, k-Nearest Neighbours (kNN) with Euclidean distance algorithm is implemented. An enhancement version for kNN algorithm, k-General Nearest Neighbours (kGNN) have been proposed at initial stage. …”
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Features Extraction of Arabic Calligraphy using extended Triangle Model for Digital Jawi Paleography Analysis
Published 2013“…For further verification, two Supervised Machine Learning (SML) and three Unsupervised Machine Learning (UML) algorithms were experimented. …”
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Malaysian license plate recognition system using Convolutional Neural Network (CNN) on web application / Nur Farahana Mahmud
Published 2022“…Nowadays, there are numerous license plate recognition systems that have been developed and analysed effectively by previous researchers using different machine learning algorithms. However, according to a recent study, ANN algorithms require a huge amount of training data while BPFFNN algorithms only have an average success rate of 70% in recognizing all the characters. …”
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Student Project -
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A Location-Based Fraud Detection in Shipping Industry Using Machine Learning Comparison Techniques
Published 2025Book chapter -
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An ensemble of neural network and modified grey wolf optimizer for stock prediction
Published 2019“…Widespread models like Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Evolutionary Strategy (ES) and Population-Based Incremental Learning (PBIL) dealing with the specified problems are also explored and compared. …”
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