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1
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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2
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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3
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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4
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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Optimization of stiffened panel fatigue life by using finite element analysis
Published 2020“…The screening approach that is the random sampling method was able to select design points close to the objective. The multi-objective genetic algorithm which selects the design points based on Pareto optimal design combined with the adaptive multi-objective algorithm method which uses an optimal space-filling was shown to be efficient for time limitation and budget. …”
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6
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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7
Optimizing Visual Surveillance Sensor Coverage Using Dynamic Programming
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Enhanced ABC-LSSVM For Energy Fuel Price Prediction
Published 2014“…To evaluate the effi ciency of the proposed model, crude oil prices data was employed as empirical data and a comparison against four approaches were conducted, which include standard ABC-LSSVM, Genetic Algorithm-LSSVM (GA-LSSVM), Cross Validation-LSSVM (CV-LSSVM), and conventional Back Propagation Neural Network (BPNN). …”
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Modified anfis architecture with less computational complexities for classification problems
Published 2018“…The proposed ANFIS model is trained by one of the metaheuristics approach instead of standard two pass learning algorithm. …”
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10
Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm
Published 2025“…In addition, to validate the prediction performance of the proposed LSA + LSTM model, extensive comparisons are performed with other popular optimization-based deep learning methods including artificial bee colony (ABC) based LSTM (ABC + LSTM), gravitational search algorithm (GSA) based LSTM (GSA + LSTM), and particle swarm optimization (PSO) based LSTM (PSO + LSTM) model using different error matrices. …”
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SVM for network anomaly detection using ACO feature subset
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A comparative study of MPPT and voltage regulator controllers for controlling output voltage in PV applications
Published 2019“…Many algorithms have been developed for the maximum power point tracking (MPPT) of solar panels. …”
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13
Power system network splitting and load frequency control optimization using ABC based algorithms / Kanendra Naidu a/l Vijyakumar
Published 2015“…The online wavelet filter is further implemented to filter out the noise in the LFC model. The IEEE 30-bus, 39-bus and 118-bus test system are chosen to validate the proposed method in MATLAB.…”
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14
Multifunctional optimized group method data handling for software effort estimation
Published 2022“…Group Method of Data Handling (GMDH) algorithms have been widely used for modelling and identifying complex systems and potentially applied in software effort estimation. …”
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15
Modified firefly algorithm for directional overcurrent relay coordination in power system protection / Muhamad Hatta Hussain
Published 2020“…Comparative studies have been conducted with respect to Multi-Objective Modified Firefly Algorithm (MOMFA), Multi-Objective Artificial Bees Colony (MOABC) and Multi-Objective Particle Swarm Optimization (MOPSO). …”
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Analysis and evaluation of various aspects of solar radiation in the Palestinian territories
Published 2023“…These coefficients were calculated using both MATLAB's fitting tool and genetic algorithm. Linear, quadratic and linear-algorithmic regression models displayed almost identical results. …”
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Eccentricity Optimization of NGB System by using Multi-Objective Genetic Algorithm
Published 2009“…Boundary equations are set by introducing feasible area to avoid improper individuals followed by utilization of some operators such as selection, mutation, crossover and elite genetic algorithm. …”
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Analysis and evaluation of various aspects of solar radiation in the Palestinian territories
Published 2013“…These coefficients were calculated using both MATLAB's fitting tool and genetic algorithm. Linear, quadratic and linear-algorithmic regression models displayed almost identical results. …”
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Optimal variational mode decomposition and integrated extreme learning machine for network traffic prediction
Published 2021“…A Scalable Artificial Bee Colony (SABC) algorithm which has fewer adjustable parameters and can thus guarantee the accuracy and stability of the prediction mechanism is also proposed. …”
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