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An adaptive ant colony optimization algorithm for rule-based classification
Published 2020“…The algorithm’s performance was compared with other variants of Ant-Miner and state-of-the-art rules-based classification algorithms based on classification accuracy and model complexity. …”
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2
Adaptive parameter control strategy for ant-miner classification algorithm
Published 2020“…This paper presents a new hybrid Ant-Miner classification algorithm and ant colony system (ACS), called ACS-Ant Miner. …”
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Rule pruning techniques in the ant-miner classification algorithm and its variants: A review
Published 2018“…Rule-based classification is considered an important task of data classification.The ant-mining rule-based classification algorithm, inspired from the ant colony optimization algorithm, shows a comparable performance and outperforms in some application domains to the existing methods in the literature.One problem that often arises in any rule-based classification is the overfitting problem. …”
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Hybrid ant colony optimization and genetic algorithm for rule induction
Published 2020“…In this study, a hybrid rule-based classifier namely, ant colony optimization/genetic algorithm ACO/GA is introduced to improve the classification accuracy of Ant-Miner classifier by using GA. …”
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Early diabetes risk prediction using Ant Colony Optimization algorithm / Nur Aisyatul Husna Ahmad Yusri and Rizauddin Saian
Published 2023“…The ACO-based classification algorithm, Ant-Miner is used to train the diabetes dataset of 520 new diabetes or potential diabetes patients from Sylhet Diabetes Hospital in Sylhet, Bangladesh. …”
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6
A new ant based rule extraction algorithm for web classification
Published 2011“…Ant-Miner algorithm is also still lacking in efficiency, accuracy and rule simplicity because of the local minima problem.Therefore, the Ant-Miner algorithm needs to be improved by taking into consideration of the accuracy and rule simplicity criteria so that it could be used to classify Web documents data sets or any large data sets.The best attribute selection method for Web texts categorization is the combination of correlation-based evaluation with random search as the search method.However, this attribute selection method will not give the best performance in attributes reduction. …”
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Classification of Cervical Cancer Using Ant-Miner for Medical Expertise Knowledge Management
Published 2018“…In this paper, an ant colony optimization based classification algorithm, Ant-Miner is applied to analyze the cervical cancer data set. …”
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Bee colony optimisation of the travelling salesman problem in light rail systems
Published 2019“…The study reported in this paper aimed to identify the most efficient algorithm and develop a mathematical model based on artificial bee colony optimisation to solve this problem in light rail transit systems. …”
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LSSVM parameters tuning with enhanced artificial bee colony
Published 2014“…The proposed model was employed in predicting financial time series data and comparison is made against the standard Artificial Bee Colony (ABC) and Cross Validation (CV) technique.The simulation results assured the accuracy of parameter selection, thus proved the validity in improving the prediction accuracy with acceptable computational time.…”
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Hybrid Artificial Bees Colony algorithms for optimizing carbon nanotubes characteristics
Published 2018“…Optimization is a crucial process to select the best parameters in single and multi-objective problems for manufacturing process.However,it is difficult to find an optimization algorithm that obtain the global optimum for every optimization problem.Artificial Bees Colony (ABC) is a well-known swarm intelligence algorithm in solving optimization problems.It has noticeably shown better performance compared to the state-of-art algorithms.This study proposes a novel hybrid ABC algorithm with β-Hill Climbing (βHC) technique (ABC-βHC) in order to enhance the exploitation and exploration process of the ABC in optimizing carbon nanotubes (CNTs) characteristics.CNTs are widely used in electronic and mechanical products due to its fascinating material with extraordinary mechanical,thermal,physical and electrical properties. …”
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11
Crytojacking Classification based on Machine Learning Algorithm
Published 2024journal::journal article -
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Ant colony optimization for rule induction with simulated annealing for terms selection
Published 2012“…Seventeen data sets which consist of discrete and continuous data from a UCI repository are used to evaluate the performance of the proposed algorithm.Promising results are obtained when compared to the Ant-Miner algorithm and PART algorithm in terms of average predictive accuracy of the discovered classification rules.…”
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A class skew-insensitive ACO-based decision tree algorithm for imbalanced data sets
Published 2021“…This study proposed an enhanced algorithm called hellingerant-tree-miner (HATM) which is inspired by ant colony optimization (ACO) metaheuristic for imbalanced learning using decision tree classification algorithm. …”
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Transfer learning in near infrared spectroscopy for stingless bee honey quality prediction across different months
Published 2024“…Thus, this study aims to evaluate the feasibility of homogenous transfer learning approaches to overcome data constraints in developing NIRS predictive models of stingless bee honey qualities across different months. …”
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Implementation of machine learning algorithm in preventing network congestion
Published 2023text::Final Year Project -
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A numerical method for frequent pattern mining
Published 2009“…The PC_Miner algorithm traverses the PC_Tree by using an efficient pruning technique. …”
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Enhanced ABD-LSSVM for energy fuel price prediction
Published 2013“…This paper presents an enhanced Artificial Bee Colony (eABC)based on Lévy Probability Distribution (LPD) and conventional mutation. …”
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Adaptive method to improve web recommendation system for anonymous users
Published 2011“…The first is iPACT, an improved recommendation system based on PACT methodology to demonstrate the prediction accuracy of the proposed enhanced classification algorithm in this research. …”
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Optimizing Visual Surveillance Sensor Coverage Using Dynamic Programming
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