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Development Of Artificial Bee Colony (Abc) Variants And Memetic Optimization Algorithms by Sulaiman, Noorazliza

“…The modified ABC variants have been developed by inserting new processing stages into the standard ABC algorithm and modifying the employed-bees and onlooker-bees phases to balance out the exploration and exploitation capabilities of the algorithm. …”
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PhABC: A Hybrid Artificial Bee Colony Strategy for Pairwise test suite Generation with Constraints Support by Alazzawi, A.K., Rais, H.M., Basri, S., Alsariera, Y.A.

“…Various existing research works were developed using a meta-heuristic algorithm as a basis for pairwise testing strategies. …”
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PhABC: A Hybrid Artificial Bee Colony Strategy for Pairwise test suite Generation with Constraints Support by Alazzawi, A.K., Rais, H.M., Basri, S., Alsariera, Y.A.

“…Various existing research works were developed using a meta-heuristic algorithm as a basis for pairwise testing strategies. …”
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Enhanced Honey Bees Colony Algorithms For Protein Tertiary Structure Prediction by Bahamish, Hesham Awadh Abdallah

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Hybrid Artificial Bees Colony algorithms for optimizing carbon nanotubes characteristics by Mohammad Jarrah, Mu'ath Ibrahim

“…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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A quick gbest guided artificial bee colony algorithm for stock market prices prediction by Shah, Habib, Tairan, Nasser, Garg, Harish, Ghazali, Rozaida

“…The objective of this work is to present a Quick Gbest Guided artificial bee colony (ABC) learning algorithm to train the feedforward neural network (QGGABC-FFNN) model for the prediction of the trends in the stock markets. …”
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A hybrid of integer differential bees and flux balance analysis for improving succinate and lactate production by Arieef, Mohd Fahmi, Kasim, Shahreen, Yee, Wen Choon, Mohamad, Mohd Saberi, Deris, Safaai, Napis, Suhaimi, Kasim, Shahreen

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A hybrid of integer differential bees and flux balance analysis for improving succinate and lactate production by Arieef, Mohd Fahmi, Yee, Wen Choon, Mohamad, Mohd Saberi, Deris, Safaai, Napis, Suhaimi, Kasim, Shahreen

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Adopting Bees Algorithm for Sequenced Based T-Way Test Data Generation by Kamal Z., Zamli, Mohd Hazli, Mohammed Zabil

“…Using combinatorial method, our strategy adopted Bees Algorithm (BA) to generate the test data for sequence t-way. …”
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Optimal distributed generation and load shedding scheme using artificial bee colony- hill climbing algorithm considering voltage stability and losses indices by Ali Abdallah, Ali Emhemed

“…The proposed solution is based on the optimization method developed from a combination of the Artificial Bee Colony and Hill Climbing algorithms (ABC-HC) to give the optimal placement and sizing of DG units to be deployed in the system. …”
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ZigBee environment for indoor localization by Chieh K.S., Keong N.Y., Burhan M.F., Balasubramaniam N., Din N.M.

Systematic Review of Enhancement of Artificial Bee Colony Algorithm Using Ant Colony Pheromone by Alaidi A.H., Der C.S., Leong Y.W.

“…The artificial bee colony (ABC) is a well-studied algorithm developed to solve continuous function optimization problems by Karboga and Akay in 2009. …”

Adaptive glioblastoma detection using evolutionary-based algorithm / Nurul Amira Mohd Ali by Mohd Ali, Nurul Amira

“…Artificial Bee Colony algorithm has been selected as the algorithm used in segmenting the brain tumor from MRI image. …”
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Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain by Mohamad Zihin , Mohd Zain

“…An improved version of Differential Evolution (DE) namely Backtracking Search Algorithm (BSA) is applied to several fed batch fermentation problems and its performance is compared with recent emerging metaheuristics such as Artificial Algae Algorithm (AAA), Artificial Bee Colony (ABC), Covariance Matrix Adaptation Evolution Strategy (CMAES) and DE. …”
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Hybridization Of Deterministic And Metaheuristic Approaches In Global Optimization by Goh, Khang Wen

“…Besides that, the comparison results also indicated that the numerical performance of the new developed methods converges faster than the original ABC algorithm. …”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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Fruit-Fly Based Searching Algorithm For Cooperative Swarming Robotic System by Abidin, Zulkifli Zainal

“…In this thesis, a simple framework and methodology in developing a bio-inspired algorithm for cooperative swarming robotic application has been developed. …”
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Intelligent Evolutionary Controller for Flexible Robotic Arm by Annisa, Jamali, Intan Z., Mat Darus

“…The controller algorithm has been formulated for trajectory planning control and vibration cancelation utilizing intelligent evolutionary algorithms such as Particle Swarm Algorithm and Artificial Bees Colony. …”
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Localisation of inspection probes in a storage tank by Rosli, Nurmi Elisya, Sophian, Ali, Ashraf, Arselan

“…The techniques that can give some better performances in terms of accuracy have been investigated and developed. In this paper, ZigBee IEEE 802.15.4 wireless communication protocols are used to implement an indoor localization application system. …”
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Data normalization techniques in swarm-based forecasting models for energy commodity spot price by Yusof, Yuhanis, Mustaffa, Zuriani, Kamaruddin, Siti Sakira

“…Data mining is a fundamental technique in identifying patterns from large data sets.The extracted facts and patterns contribute in various domains such as marketing, forecasting, and medical.Prior to that, data are consolidated so that the resulting mining process may be more efficient.This study investigates the effect of different data normalization techniques.which are Min-max, Z-score and decimal scaling, on Swarm-based forecasting models.Recent swarm intelligence algorithms employed includes the Grey Wolf Optimizer (GWO) and Artificial Bee Colony (ABC).Forecasting models are later developed to predict the daily spot price of crude oil and gasoline.Results showed that GWO works better with Z-score normalization technique while ABC produces better accuracy with the Min-Max.Nevertheless, the GWO is more superior than ABC as its model generates the highest accuracy for both crude oil and gasoline price.Such a result indicates that GWO is a promising competitor in the family of swarm intelligence algorithms.…”
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