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Improving amphetamine-type stimulants drug classification using chaotic-based time-varying binary whale optimization algorithm
Published 2022“…Firstly, a non-linear time-varying modified Sigmoid transfer function is used as the binarization method. Second, a hybrid Logistic-Tent chaotic map is employed to substitute the pseudorandom numbers of the probability operator in standard WOA. …”
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Article -
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Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals
Published 2020“…In this regard, this thesis proposes five FS methods for efficient EMG signals classification. The first method is the Binary Tree Growth Algorithm (BTGA), which implements a hyperbolic tangent function to convert the Tree Growth Algorithm into the binary version. …”
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Thesis -
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Hybrid binary whale with harris hawks for feature selection
Published 2022“…A tremendous flow of big data has come from the growing use of digital technology and intelligent systems. …”
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Simulation on Emotion Recognition for Autism Therapy
Published 2017“…This paper mainly focusing on the simulation of emotion recognition software based on the Local Binary Pattern (LBP) algorithm to extract the features from the image. …”
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Final Year Project -
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Named entity recognition using a new fuzzy support vector machine.
Published 2008“…In our method we have employed Support Vector Machine as one of the best machine learning algorithm for classification and we contribute a new fuzzy membership function thus removing the Support Vector Machine’s weakness points in NER precision and multi classification. …”
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Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier
Published 2018“…Due to the current methods in feature extraction are still improving, this project proposed a new feature extraction method to increase the performance of iris classification. In this project, a classification system is proposed with the one-dimensional local binary pattern algorithm (1D-LBP) with the K-Nearest Neighbour (K-NN) classifier and the system is developed by using a Raspberry Pi 3.There are eight different subjects used to classify in this classification system and each subject consists of seven samples of normalized iris image as input to the system. …”
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Monograph -
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Task-state EEG signal classification for spatial cognitive evaluation based on multiscale high-density convolutional neural network
Published 2022“…The MHCNN classification method proposed in this research could be used as an effective biological indicator of spatial cognitive training effect and could be extended to other brain function evaluations.…”
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Performances of machine learning algorithms for binary classification of network anomaly detection system
Published 2018“…The finding showed that AODE algorithm is performed well in term of accuracy and processing time for binary classification towards UNSW-NB15 dataset.…”
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Conference or Workshop Item -
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Feature Selection using Binary Simulated Kalman Filter for Peak Classification of EEG Signals
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Conference or Workshop Item -
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Classification System for Wood Recognition using K-Nearest Neighbor with Optimized Features from Binary Gravitational Algorithm
Published 2014“…The project proposes a classification system using Gray Level Co-Occurrence Matrix (GLCM) as feature extractor, K-Nearest Neighbor (K-NN) as classifier and Binary Gravitational Search Algorithm (BGSA) as the optimizer for GLCM’s feature selection and parameters. …”
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Conference or Workshop Item -
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Development of compound clustering techniques using hybrid soft-computing algorithms
Published 2006“…The neural network methods use a number of heuristics to find appropriate parametric values. …”
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Monograph -
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Modelling of default risk for home credit data using machine learning approach
Published 2022“…The banking industry plays an essential role in the financial system and economy of a nation. As a key component in the financial system, banks mainly function as the allocator of funds from savers to debtors. …”
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Thesis -
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A study on component-based technology for development of complex bioinformatics software
Published 2004“…The second layer uses discriminative SVM algorithm with a state-of-the-art string kernel based on PSI-BLAST profiles that is used to leverage the unlabeled data. …”
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Monograph -
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Enhanced Multi-Objective Grey Wolf Optimizer with Lévy Flight and Mutation Operators for Feature Selection
Published 2023“…As feature selection is a binary problem, the continuous search space is converted into a binary space using the sigmoid function. To evaluate the classification performance of the selected feature subset, the proposed approach employs a wrapper-based Artificial Neural Network (ANN). …”
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Postal address handwritten recognition using convolutional neural network / Nur Hasyimah Abd Aziz
Published 2020“…Functionality test was done in order to evaluate the system. …”
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Thesis -
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Hybrid ensemble learning techniques for intrusion detection systems in Internet of Things security
Published 2025“…This research developed three techniques to tackle challenges a large number of features, extensive datasets, data quality issues, and imbalanced classes in both binary and multi-class classifications. The first technique employed the XGBoost and LightGBM algorithms to solve a binary classification problem across seven different datasets. …”
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