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Application of the bees algorithm to the selection features for manufacturing data
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Hybrid of swarm intelligent algorithms in medical applications
Published 2019“…The effectiveness of hybrid swarm intelligent algorithms was studied since no single algorithm is effective in solving all types of problems. …”
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Test Data Generation for Event Driven System Using Bees Algorithm
Published 2013“…In this paper we discuss and proposed a new strategy for generating test data for event-driven system using a bio inspired artificial intelligent, namely Bees Algorithm (BA). …”
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An application of hybrid swarm intelligence algorithms for dengue outbreak prediction
Published 2019“…Concerning this matter, this study presents an application of hybrid Swarm Intelligence (SI) algorithms for a dengue outbreak prediction. …”
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Neural network training using hybrid particle-move artificial bee colony algorithm for pattern classification
Published 2017“…The Artificial Neural Networks Training (ANNT) process is an optimization problem of the weight set which has inspired researchers for a long time. By optimizing the training of the neural networks using optimal weight set, better results can be obtained by the neural networks.Traditional neural networks algorithms such as Back Propagation (BP) were used for ANNT, but they have some drawbacks such as computational complexity and getting trapped in the local minima.Therefore, evolutionary algorithms like the Swarm Intelligence (SI) algorithms have been employed in ANNT to overcome such issues.Artificial Bees Colony (ABC) optimization algorithm is one of the competitive algorithms in the SI algorithms group. …”
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A quick gbest guided artificial bee colony algorithm for stock market prices prediction
Published 2018“…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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Data normalization techniques in swarm-based forecasting models for energy commodity spot price
Published 2014“…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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Hybridized Intelligent Neural Network Optimization Model for Forecasting Prices of Rubber in Malaysia
Published 2023“…These algorithms, including Grey Wolf Optimization Algorithm, Artificial Bee Colony Algorithm, and Particle Swarm Optimization Algorithm were utilized in the forecasting data analysis. …”
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Hybridized Intelligent Neural Network Optimization Model for Forecasting Prices of Rubber in Malaysia
Published 2023“…These algorithms, including Grey Wolf Optimization Algorithm, Artificial Bee Colony Algorithm, and Particle Swarm Optimization Algorithm were utilized in the forecasting data analysis. …”
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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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A novel hybrid metaheuristic algorithm for short term load forecasting
Published 2017“…With respect to that matter, this study presents a hybrid Least Squares Support Vector Machines (LSSVM) with a rather new Swarm Intelligence (SI) algorithm namely Grey Wolf Optimizer (GWO). …”
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Enhanced artificial bee colony for training least squares support vector machines in commodity price forecasting
Published 2014“…By using commodities prices time series as empirical data, the proposed technique is compared against two techniques, including Back Propagation Neural Network and by Genetic Algorithm.Empirical results show the capability of the proposed technique in producing higher prediction accuracy for the prices of interested time series data.…”
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Hybrid Metaheuristic Algorithm for Short Term Load Forecasting
Published 2016“…With respect to that matter, this study presents a hybrid Least Squares Support Vector Machines (LSSVM) with a rather new Swarm Intelligence (SI) algorithm namely Grey Wolf Optimizer (GWO). …”
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Artificial intelligence in sustainability reporting / Prof. Dr Corina Joseph
Published 2023“…In the speech introduction, various definitions of Artificial Intelligence (AI) were provided. One of these definitions describes AI as the utilization of automated algorithms, robotics, or machines that mimic human cognitive functions, enabling them to perform tasks such as learning, identifying, analyzing, and problem-solving (Graham et al., 2020). …”
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Hybrid Sine Cosine and Fitness Dependent Optimizer for global optimization
Published 2021“…The fitness-dependent optimizer (FDO), a newly proposed swarm intelligent algorithm, is focused on the reproductive mechanism of bee swarming and collective decision-making. …”
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