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Optimisation of Surface Roughness in 3D Printing Using the Bees Algorithm
Published 2025“…The focus of this study is to determine the optimum input parameter of the 3D printer using the Bees Algorithm (BA). This study uses the Bees Algorithm to predict the best combination parameters to optimise the surface roughness of parts printed by a fused deposition modelling (FDM) machine. …”
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Book Chapter -
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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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Thesis -
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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“…At first the model selects the suitable biases and weights utilizing a hybrid (ABC) and (DA). …”
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Optimal timber transportation planning in tropical hill forest using bees algorithm
Published 2022“…This study proposed a multi-objective linear programming model with Bees algorithm (BA) to find an optimal cost TTP for extraction, forest road, and landing locations. …”
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LSSVM parameters tuning with enhanced artificial bee colony
Published 2014“…To guarantee its convincing performance, it is crucial to select an appropriate technique in order to obtain the optimized hyper-parameters of LSSVM algorithm.In this paper, an Enhanced Artificial Bee Colony (eABC) is used to obtain the ideal value of LSSVM’s hyper parameters, which are regularization parameter, γ and kernel parameter, σ2.Later, LSSVM is used as the prediction model. …”
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Embedded fuzzy classifier for detection and classification of preseizure state using real EEG data
Published 2014“…Therefore, the work presented here includes embedded hardware system that works with classification algorithm on real EEG signals, in a ubiquitous setting. …”
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Embedded Fuzzy Classifier for Detection and Classification of Preseizure state using Real EEG data
Published 2014“…Therefore, the work presented here includes embedded hardware system that works with classification algorithm on real EEG signals, in a ubiquitous setting. …”
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Improved cuckoo search based neural network learning algorithms for data classification
Published 2014“…Finally, the proposed CS hybrid variants such as; HACPSO, HACPSO-BP, HACPSO-LM, CSBP, CSLM, CSERN, and CSLMERN are evaluated and compared with conventional Back propagation Neural Network (BPNN), Artificial Bee Colony Neural Network (ABCNN), Artificial Bee Colony Back propagation algorithm (ABC-BP), and Artificial Bee Colony Levenberg-Marquardt algorithm (ABC-LM). …”
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Thesis -
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Metaheuristic based ids using multi-objective wrapper feature selection and neural network classification
Published 2021“…The classifier, named as HADMLP is trained using a hybridization of the artificial bee colony along with the dragonfly algorithm. A multi-objective artificial bee colony model which is wrapper-based is used for selection of feature. …”
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Conference or Workshop Item -
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Embedded Fuzzy Classifier for Detection and Classification of Preseizure State Using Real EEG Data
Published 2013“…Therefore, the work presented here includes embedded hardware system that works with classification algorithm on real EEG signals, in a ubiquitous setting. …”
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VHDL modeling of EMG signal classification using artificial neural network
Published 2012“…A back-propagation neural network with Levenberg-Marquardt training algorithm has been used for the classification of EMG signals. …”
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Artificial Bee Colony for Minimizing the Energy Consumption in Mobile Ad Hoc Network
Published 2019“…This algorithm works on minimizing the average energy consumption of the selected route. …”
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Feature-based face recognition system using utilized artificial neural network
Published 2010“…This project aims to reduce the effect of critical conditions such as excessive illumination, facial expressions, hairstyles, beard and moustache which have affected the performance of face recognition since ages ago. The main contributions of this project are the automatic algorithms for mouth detection, facial features cropping and face classification. …”
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Classification of transient facial wrinkle
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Data Classification and Its Application in Credit Card Approval
Published 2004“…This project is involved with identification of the available algorithms used in data classification and the implementation of C4.5 decision tree induction algorithm in solving the data classifying task. …”
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Final Year Project -
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Hybridization of enhanced ant colony system and Tabu search algorithm for packet routing in wireless sensor network
Published 2020“…Better performances were also achieved for success rate, throughput, and latency when compared to other hybrid routing algorithms such as Fish Swarm Ant Colony Optimization (FSACO), Cuckoo Search-based Clustering Algorithm (ICSCA), and BeeSensor-C. …”
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Region-based segmentation and classification of Mandibular First Molar Tooth based on Demirjian’s method
Published 2020“…Traditionally, dental age assessment is done by applying the scoring system based on tooth development from the x-ray image. …”
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