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An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani
Published 2015“…This research is mainly about improving existing classification algorithms for a correct classification results and evaluating the accuracy of classification algorithms in correctly determining urban growth forms, The datasets are Landsat Thematic Mapper (TM) images of Klang Valley, one of the most rapid urban growth areas in Malaysia. …”
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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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An efficient intrusion detection model based on hybridization of artificial bee colony and dragonfly algorithms for training multilayer perceptrons
Published 2020“…This study proposes a new binary classification model for intrusion detection, based on hybridization of Artificial Bee Colony algorithm (ABC) and Dragonfly algorithm (DA) for training an artificial neural network (ANN) in order to increase the classification accuracy rate for malicious and non-malicious traffic in networks. …”
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Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam
Published 2017“…For a fair performance evaluation, the selection of the best peak model requires experimental exploration by using a common and unbiased classification approach. …”
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Binary ant colony optimization algorithm in learning random satisfiability logic for discrete hopfield neural network
Published 2024“…This study introduced a novel ant colony optimization algorithm that implements the population selection strategy of the Estimation of Distribution Algorithm and a new pheromone updating formula. …”
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Hybrid Binary Grey Wolf with Harris Hawks Optimizer for Feature Selection
Published 2021“…A wrapper-based k-Nearest neighbor is used to evaluate the goodness of the selected features. …”
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Hybrid binary grey Wolf with Harris hawks optimizer for feature selection
Published 2021“…A wrapper-based k-Nearest neighbor is used to evaluate the goodness of the selected features. …”
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Hybrid binary grey Wolf with Harris hawks optimizer for feature selection
Published 2021“…A wrapper-based k-Nearest neighbor is used to evaluate the goodness of the selected features. …”
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Machine learning approach of predicting Airline flight delay using Naïve Bayes Algorithm / Ahmad Adib Baihaqi Shukri ... [et al.]
Published 2024“…This study aims to study the Naïve Bayes algorithm for flight delay prediction. The objective is to develop a reliable flight delay prediction model using the Naïve Bayes algorithm and evaluate its performance. …”
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Airline flight delay prediction using Naïve Bayes algorithm / Ahmad Adib Baihaqi Shukri
Published 2024“…This study aims to study the Naïve Bayes algorithm for flight delay prediction. The objective is to develop a reliable flight delay prediction model using the Naïve Bayes algorithm and evaluate its performance. …”
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Multi-label risk diabetes complication prediction model using deep neural network with multi-channel weighted dropout
Published 2025“…Comparative evaluations with existing dropout methods demonstrated the superior performance of the proposed technique, particularly when applied within the Algorithm Adaptation framework using DNNs. …”
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Face recognition for varying illumination and different optical zoom using a combination of binary and geometric features
Published 2020“…The proposed method consists of five main stages, starting with eye area detection using the developed Viola-Jones algorithm. Next, the iris is detected using the Circular Hough Transform (CHT) method and will convert it into binary using the proposed Columnar Binary Conversion (CBC) method to preserve the appearance of the facial features under the illumination variation. …”
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Opposition Based Competitive Grey Wolf Optimizer For EMG Feature Selection
Published 2020“…As for EMG feature selection, the proposed algorithms are evaluated using the EMG data acquired from the publicly access EMG database. …”
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Malaysian license plate recognition system using Convolutional Neural Network (CNN) on web application / Nur Farahana Mahmud
Published 2022“…The binary image of the extracted characters was fed to the CNN model for classification. …”
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Multitasking deep neural network models for Arabic dialect sentiment analysis
Published 2022“…So far, there has been no effort to handle the negation context in Arabic using a deep neural network. The existing approaches are based on traditional machine learning algorithms, such as support vector machine (SVM). …”
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Multiclass Convolution Neural Network For Classification Of Covid-19 Ct Images
Published 2024journal::journal article -
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Prediction of cause of death from forensic autopsy reports using text classification techniques: A comparative study
Published 2018“…Finally, classification model performance was evaluated using four performance measures i.e. overall accuracy, macro precision, macro-F-measure, and macro recall. …”
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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“…There are a lot of feature extraction methods and classification methods for iris classification. Classic local binary pattern (LBP) is one of the most useful feature extraction methods. …”
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