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Bees algorithm for Forest transportation planning optimization in Malaysia
Published 2021“…Examples of algorithm that are finding their way to the forest transportation planning problem include Genetic Algorithm (GA), Particle Swarm Optimization (PSO) algorithm, Ant Colony Optimization (ACO) algorithm, Simulated Annealing (SA) algorithm and Tabu Search (TS) algorithm. …”
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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“…This study combined models such as the artificial neural network (ANN) algorithm with the Firefly algorithm (FA) and Artificial Bee Colony (ABC) optimization techniques for the estimation of monthly SL values in the �oruh River in Northeastern Turkey. …”
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Minimizing power loss using modified artificial bee colony algorithm / Nur Azlin Ashiqin Mohd Amin ...[et al.]
Published 2021“…In this paper, the Modified Artificial Bee Colony (MABC) algorithm is implemented to solve the power system's optimal reactive power flow problem. …”
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Optimizing timber transportation planning for timber harvesting using bees algorithm in Malaysia
Published 2023“…Two types of extraction machines with unique characteristics to be applied in timber harvest area in Malaysia is combined for timber harvesting with the aim each machine will extract timber suitable to their ability. A Bees Algorithm (BA) was proposed to find an optimum TTP for timber extraction, forest road, and landing locations with grid cell-sized 10 m × 10 m and attributed with fixed and variable costs. …”
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HABC: Hybrid artificial bee colony for generating variable T-way test sets
Published 2020“…This paper proposed a hybrid artificial bee colony (HABC) strategy based on the hybrid artificial bee colony algorithm and practical swarm optimization to generate optimal test suite of variable strength interaction. …”
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HABC: Hybrid artificial bee colony for generating variable T-way test sets
Published 2020“…This paper proposed a hybrid artificial bee colony (HABC) strategy based on the hybrid artificial bee colony algorithm and practical swarm optimization to generate optimal test suite of variable strength interaction. …”
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Acoustic emission partial discharge localization in oil based on artificial bee colony
Published 2025“…The study concludes that the ABC is more suitable for the multi-variable PD localization task than the GA, PSO, and BA due to its effective balance between local search by onlooker bees and global exploration by scout bees.…”
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Hydroclimatic data prediction using a new ensemble group method of data handling coupled with artificial bee colony algorithm
Published 2022“…It is rare to find a hydrological application using the group method of data handling (GMDH) model, artificial bee colony (ABC) algorithm, and ensemble technique, precisely predicting ungauged sites. …”
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A new algorithm for normal and large-scale optimization problems: Nomadic People Optimizer
Published 2019“…The proposed and the benchmark algorithms are tested for large-scale optimization problems which are associated with high-dimensional variability. …”
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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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Differential evolution for neural networks learning enhancement
Published 2008“…These algorithms can be used successfully in many applications requiring the optimization of a certain multi-dimensional function. …”
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Algorithmic design issues in adaptive differential evolution schemes: Review and taxonomy
Published 2018“…DE is very sensitive to its parameter settings and mutation strategy; thus, this study aims to investigate these settings with the diverse versions of adaptive DE algorithms. This study has two main objectives: (1) to present an extension for the original taxonomy of evolutionary algorithms (EAs) parameter settings that has been overlooked by prior research and therefore minimize any confusion that might arise from the former taxonomy and (2) to investigate the various algorithmic design schemes that have been used in the different variants of adaptive DE and convey them in a new classification style. …”
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Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals
Published 2020“…In this regard, this thesis proposes five FS methods for efficient EMG signals classification. The first method is the Binary Tree Growth Algorithm (BTGA), which implements a hyperbolic tangent function to convert the Tree Growth Algorithm into the binary version. …”
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Effective EEG channels for emotion identification over the brain regions using differential evolution algorithm
Published 2019“…Furthermore, the right and left occipital channels may help in identifying happiness, sadness, surprise and neutral emotional states. The DEFS_Ch algorithm raised the linear discriminant analysis (LDA) classification accuracy from 80% to 86.85%, indicating that DEFS_Ch may offer a useful way for reliable enhancement of the detection of different emotional states of the brain regions.…”
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Solving large-scale problems using multi-swarm particle swarm approach
Published 2018“…The proposed approach strived to scale up the application of the (PSO) algorithm towards solving large-scale optimization tasks of up to 1000 real-valued variables. …”
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Intersection Features For Android Botnet Classification
Published 2019“…The Chi Square was used to select the most significant permissions, then the classification algorithms like Naïve Bayes and Decision Tree were used to classify the Android apps as botnet or benign apps. …”
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Feature selection optimization using hybrid relief-f with self-adaptive differential evolution
Published 2017“…Hence, feature selection is embedded to select the most meaningful features based on their rank. Differential evolution (DE) is one of the evolutionary algorithms that are widely used in various classification domains. …”
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