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Group method of data handling with artificial bee colony in combining forecasts
Published 2018“…The weights for each individual model are calculated using ABC algorithm. In order to evaluate the proposed model, this study tested the proposed model on the International Airline Passengers data, and the performances are calculated using mean square error (MSE), mean average error (MAE) and mean average percentage error (MAPE). …”
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Binary Artificial Bee Colony Optimization For Weighted Random 2 Satisfiability In Discrete Hopfield Neural Network
Published 2023“…This thesis will be presented by implementing simulated, and benchmark data sets with multiple performance evaluation metrics. Based on the findings, the proposed model outperforms other models.…”
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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“…In addition, four types of intrusion detection evaluation datasets were applied to evaluate the proposed model in comparison to the others. …”
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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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5
Multi-Class Multi-Level Classification of Mental Health Disorders Based on Textual Data from Social Media
Published 2024“…The results of the experiments show that the MCML classification algorithm successfully performs detailed classification and produces promising results for each classification level. …”
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Sediment load forecasting from a biomimetic optimization perspective: Firefly and Artificial Bee Colony algorithms empowered neural network modeling in �oruh River
Published 2025“…The estimation of SL values was achieved using inputs of previous SL and streamflow values provided to the models. Various statistical metrics were used to evaluate the accuracy of the established hybrid and stand-alone models. …”
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Performance analysis of ZigBeePRO network using shortest path algorithm for Distributed Renewable Generation
Published 2021“…The other performance parameters, including network throughput, data loss, and ZigBeePRO collision, are also evaluated.…”
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Parameter estimation of essential amino acids in Arabidopsis thaliana using hybrid of bees algorithm and harmony search
Published 2019“…Global optimization methods can be applied by minimizing the distance between experimental data and predicted models. This paper proposes the Hybrid of Bees Algorithm and Harmony Search (BAHS) to estimate the kinetics parameters of essential amino acid production in the aspartate metabolism for Arabidopsis thaliana. …”
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Book Chapter -
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Symmetric Key Size for Different Level of Information Classification
Published 2006“…Confidential information can be categorized into various levels of classification. The classification depends on the level of damage to an organization or to national security when the information is disclosed. …”
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Performance analysis of machine learning algorithms for classification of infection severity levels on rubber leaves
Published 2023“…This work shows that the spectroscopic measurement combined with classification techniques are promising strategy to classify severity level of WRD based on the spectral data of the rubber leaves.…”
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Correlation Feature Selection Weighting Algorithms for Better Support Vector Classification: An Empirical Study
Published 2020“…Prediction and/or classification accuracies of cfsw-SVM algorithms are significantly improved.…”
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Comparative analysis of spiral dynamic algorithm and artificial bee colony optimization for position control of flexible link manipulators
Published 2024“…This study aims to evaluate the effectiveness of two optimization algorithms, artificial bee colony (ABC) and spiral dynamic algorithm (SDA), in controlling the position of a flexible-link manipulator. …”
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Deterministic and stochastic inventory routing problems with backorders using artificial bee colony / Huda Zuhrah Ab Halim
Published 2019“…A new MILP for DSIRPB is formulated and used within the algorithm. The DSIRPB is modeled as stochastic dynamic programming and solved using hybrid rollout algorithm. …”
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Automatic classification of medical x-ray images
Published 2013“…These features have been exploited in different algorithms for automatic classification of medical X-ray images. …”
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Artificial Bee Colony for Minimizing the Energy Consumption in Mobile Ad Hoc Network
Published 2019“…The aim of this paper is to find the best possible route from the source to the destination based on a method inspired by the searching behaviour of bee colonies, i.e. artificial bee colony (ABC) algorithm. …”
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Hybrid artificial bee colony algorithm with branch and bound for two–sided assembly line balancing
Published 2018“…Recently, the artificial bee colony (ABC) algorithm was used in the solution process where it was considered as a very useful, effective and well-known algorithm. …”
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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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Diabetes Diagnosis And Level Of Care Fuzzy Rule-Based Model Utilizing Supervised Machine Learning For Classification And Prediction
Published 2024“…Overall, the proposed fuzzy rule-based diabetes diagnosis and level of care fuzzy model works well with most of the machine learning algorithms tested. …”
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