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Enhanced artificial bee colony-least squares support vector machines algorithm for time series prediction
Published 2014“…This study proposed a hybrid algorithm, based on Artificial Bee Colony (ABC) and LSSVM, that consists of three algorithms; ABC-LSSVM, lvABC-LSSVM and cmABC-LSSVM. …”
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Time series predictive analysis based on hybridization of meta-heuristic algorithms
Published 2018“…The identified meta-heuristic methods namely Moth-flame Optimization (MFO), Cuckoo Search algorithm (CSA), Artificial Bee Colony (ABC), Firefly Algorithm (FA) and Differential Evolution (DE) are individually hybridized with a well-known machine learning technique namely Least Squares Support Vector Machines (LS-SVM). …”
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Application of LSSVM by ABC in energy commodity price forecasting
Published 2014“…The importance of the hyper parameters selection for a kernel-based algorithm, viz.Least Squares Support Vector Machines (LSSVM) has been a critical concern in literature.In order to meet the requirement, this work utilizes a variant of Artificial Bee Colony (known as mABC) for hyper parameters selection of LSSVM.The mABC contributes in the exploitation process of the artificial bees and is based on Levy mutation.Realized in crude oil price forecasting, the performance of mABC-LSSVM is guided based on Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSPE) and compared against the standard ABC-LSSVM and LSSVM optimized by Genetic Algorithm. …”
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Time series predictive analysis based on hybridization of meta-heuristic algorithms
Published 2018“…The identified meta-heuristic methods namely Moth-flame Optimization (MFO), Cuckoo Search algorithm (CSA), Artificial Bee Colony (ABC), Firefly Algorithm (FA) and Differential Evolution (DE) are individually hybridized with a well-known machine learning technique namely Least Squares Support Vector Machines (LS-SVM). …”
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Using the bees algorithm to optimise a support vector machine for wood defect classification
Published 2007“…This paper describes a new application of the Bees Algorithm to the optimization of a Support Vector Machine (SVM) for the problem of classifying defects in plywood. …”
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Gasoline price forecasting: An application of LSSVM with improved ABC
Published 2014“…Optimizing the hyper-parameters of Least Squares Support Vector Machines (LSSVM) is crucial as it will directly influence the predictive power of the algorithm.To tackle such issue, this study proposes an improved Artificial Bee Colony (IABC) algorithm which is based on conventional mutation.The IABC serves as an optimizer for LSSVM.Realized in gasoline price forecasting, the performance is guided based on Mean Absolute Percentage Error (MAPE) and Root Mean Square Percentage Error (RMSPE).The conducted simulation results show that, the proposed IABCLSSVM outperforms the results produced by ABC-LSSVM and also the Back Propagation Neural Network.…”
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Forecasting model based on LSSVM and ABC for natural resource commodity
Published 2013“…Reliable forecast of the price of natural resource commodity is of interest for a wide range of applications.This includes generating macroeconomic projections and in assessing macroeconomic risks.Various approaches have been introduced in developing the required forecasting models.In this paper, a forecasting model based on an optimized Least Squares Support Vector Machine is proposed.The determination of hyper-parameters is performed using a nature inspired algorithm, Artificial Bee Colony.The proposed forecasting model is realized is gold price forecasting.The undertaken experiments showed that the prediction accuracy and Mean Absolute Percentage Error produced by the proposed model is better compared on the one produced using Least Squares Support Vector Machine as an individual.…”
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Surface roughness optimization based on hybrid harmony search and artificial bee colony algorithm in electric discharge machining process
Published 2023“…Electric discharges; Optimal systems; Optimization; Surface roughness; Artificial bee colonies (ABC); Artificial bee colony algorithms; Convergence rates; Electric discharge machining (EDM); Hybrid approach; Numerical applications; Optimal solutions; Surface roughness (Ra); Electric discharge machining…”
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An improved dynamic load balancing for virtualmachines in cloud computing using hybrid bat and bee colony algorithms
Published 2021“…Therefore, to overcome these problems, this study proposed an improved dynamic load balancing technique known as HBAC algorithm which dynamically allocates task by hybridizing Artificial Bee Colony (ABC) algorithm with Bat algorithm. …”
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Impact of evolutionary algorithm on optimization of nonconventional machining process parameters
Published 2025“…This paper presents the optimization of laser beam machining in additive manufacturing of polymer-based material parameters, specifically focusing on cutting speed, gas pressure of nitrogen, and focal point locations, to achieve optimal mean surface roughness. …”
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Lévy mutation in artificial bee colony algorithm for gasoline price prediction
Published 2012“…In this paper, a mutation strategy that is based on Lévy Probabily Distribution is introduced in Artificial Bee Colony algorithm. …”
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An improved bees algorithm local search mechanism for numerical dataset
Published 2015“…Bees Algorithm (BA), a heuristic optimization procedure, represents one of the fundamental search techniques is based on the food foraging activities of bees. …”
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Short term forecasting based on hybrid least squares support vector machines
Published 2018“…In this study, hybrid Least Squares Support Vector Machines (LSSVM) with four meta-heuristic algorithms viz. …”
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BAT-BP: A new BAT based back-propagation algorithm for efficient data classification
Published 2016“…The performance of the proposed Bat-BP algorithm is then compared with Artificial Bee Colony using BPNN (ABC-BP), Artificial Bee Colony using Levenberg-Marquardt (ABC-LM) and BPNN algorithm. …”
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