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1
An adaptive ant colony optimization algorithm for rule-based classification
Published 2020“…Differing from other complex and difficult classification models, rules-based classification algorithms produce models which are understandable for users. …”
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An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani
Published 2015“…The urban growth images obtained are analysed to improve existing classification algorithms. The improved algorithm is constructed by adding new parameter and classification rule to existing algorithm. …”
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3
Formulating new enhanced pattern classification algorithms based on ACO-SVM
Published 2013“…This paper presents two algorithms that integrate new Ant Colony Optimization (ACO) variants which are Incremental Continuous Ant Colony Optimization (IACOR) and Incremental Mixed Variable Ant Colony Optimization (IACOMV) with Support Vector Machine (SVM) to enhance the performance of SVM.The first algorithm aims to solve SVM model selection problem. …”
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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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5
Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam
Published 2017“…In the preliminary study, the algorithm is evaluated on the four different peak models of the three EEG signals using the artificial neural network (ANN) with particle swarm optimization (PSO) as learning algorithm. …”
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6
Comparison of Logistic Regression, Random Forest, SVM, KNN Algorithm for Water Quality Classification Based on Contaminant Parameters
Published 2024“…The methodology used includes data collection, preprocessing, and algorithm implementation with evaluation using crossvalidation techniques. …”
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Classification models for higher learning scholarship award decisions
Published 2018“…A dataset of successful and unsuccessful applicants was taken and processed as training data and testing data used in the modelling process. Five algorithms were employed to develop a classification model in determining the award of the scholarship, namely J48, SVM, NB, ANN and RT algorithms. …”
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Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak
Published 2019“…The fourth stage is to design evaluation methodology of Max-Min Rule-Based Classification Algorithm using classifier model. …”
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10
Crytojacking Classification based on Machine Learning Algorithm
Published 2024journal::journal article -
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A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem
Published 2016“…There are two methods in dealing with imbalanced classification problem, which are based on data or algorithmic level. …”
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12
Sentiment analysis using negative selection algorithm for Twitter’s messages / Nazirah Che Alhadi
Published 2012“…In order to develop this model classification and prototype, 480 Twitter’s messages were used as training data and 120 Twitter’s messages for testing data to determine the accuracy of the classification model. …”
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13
Modified word representation vector based scalar weight for contextual text classification
Published 2024“…To bridge this gap, a five-phase research methodology is structured to propose and evaluate an algorithm enabling the external modification of LLM-generated word vectors using scalar values as the focus weightage. …”
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14
A New Model For Network-Based Intrusion Prevention System Inspired By Apoptosis
Published 2024thesis::doctoral thesis -
15
Fair bandwidth distribution marking and scheduling algorithm in network traffic classification
Published 2019“…This is achieved by using a new design algorithm by separating marker TCP and UDP protocols and extended the marking probability for injecting more green and yellow traffic into the network. …”
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16
A hybrid deep CNN model for fast class-incremental food classification / Aymen Taher Ahmed al-Ashwal
Published 2019“…It requires retraining the model for new classes or using transfer learning. …”
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17
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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18
The classification of wink-based eeg signals by means of transfer learning models
Published 2021“…Whilst it was observed that the optimized k-NN model based on the aforesaid pipeline could achieve a classification accuracy of 100% for the training, validation, and tes t data. …”
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19
Sentiment analysis for malay newspaper (SAMNews) using negative selection algorithm / Nur Amalina Redzuan
Published 2013“…In future, a comparative study on Artificial Immune System and other techniques or algorithms can be carried out to enhance the performance of the classification model.…”
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A novelty classification model for varied agarwood oil quality using the K-Nearest Neighbor algorithm / Aqib Fawwaz Mohd Amidon … [et al.]
Published 2022“…As a result, a new grading system based on artificial algorithms, namely K-Nearest Neighbor algorithms, was established. …”
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