Search Results - ((((((machine algorithm) OR (learning algorithm))) OR (bees algorithm))) OR (colony algorithm))

An improved artificial bee colony algorithm for training multilayer perceptron in time series prediction by Shah, Habib

“…They are: Global Guided Artificial Bee Colony (GGABC), Improved Gbest Guided Artificial Bee Colony (IGGABC) and Artificial Smart Bee Colony (ASBC) algorithm. …”
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Application of the bees algorithm for constrained mechanical design optimisation problem by Kamaruddin, Shafie, Abd Latif, Mohd Arif Hafizi

“…Nowadays, many optimisation algorithms have been introduced due to the advancement of technology such as Teaching Learning Based Optimisation (TLBO), Ant Colony Optimisation (ACO), Particle Swarm Optimisation (PSO) and the Bees Algorithm. …”
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BAT-BP: A new BAT based back-propagation algorithm for efficient data classification by Mohd. Nawi, Nazri, M. Z., Rehman, Hafifi, Nurfarian, Khan, Abdullah, Siming, Insaf Ali

“…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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Artificial bee colony optimization of interval type-2 fuzzy extreme learning system for chaotic data by Hassan, S., Jaafar, J., Khanesar, M.A., Khosravi, A.

“…This paper propose a novel hybrid learning algorithm for the design of IT2FLS. The proposed hybrid learning algorithm utilizes the combination of extreme learning machine (ELM) and artificial bee colony optimization (ABC) to tune the parameters of the consequent and antecedent parts of the IT2FLS, respectively. …”
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Enhanced artificial bee colony-least squares support vector machines algorithm for time series prediction by Zuriani, Mustaffa

“…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 by Mustaffa, Zuriani, Sulaiman, Mohd Herwan, Rohidin, Dede, Ernawan, Ferda, Kasim, Shahreen

“…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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Surface roughness optimization based on hybrid harmony search and artificial bee colony algorithm in electric discharge machining process by Deris A.M., Solemon B.

“…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…”

Enhanced artificial bee colony for training least squares support vector machines in commodity price forecasting by Mustaffa, Zuriani, Yusof, Yuhanis, Kamaruddin, Siti Sakira

“…The importance of optimizing machine learning control parameters has motivated researchers to investigate for proficient optimization techniques.In this study, a Swarm Intelligence approach, namely artificial bee colony (ABC) is utilized to optimize parameters of least squares support vector machines.Considering critical issues such as enriching the searching strategy and preventing over fitting, two modifications to the original ABC are introduced. …”
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Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS by Hassan, S., Khanesar, M.A., Jaafar, J., Khosravi, A.

“…Since extreme learning machine is a non-iterative estimation procedure, it is faster than gradient-based algorithms which are iterative. …”
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Utilizing artificial bee colony algorithm as feature selection method in Arabic text classification by Hijazi, Musab, Zeki, Akram M., Ismail, Amelia Ritahani

“…In this paper, the filter method chi square and the Artificial Bee Colony) ABC algorithm were both used as FS methods . …”
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Optimal parameters of an ELM-based interval type 2 fuzzy logic system: a hybrid learning algorithm by Hassan, S., Khanesar, M.A., Jaafar, J., Khosravi, A.

“…A disadvantage of ELM is the random generation of its hidden neuron that causes additional uncertainty, in both approximation and learning. In order to overcome this limitation in an ELM-based IT2FLS, artificial bee colony optimization algorithm is utilized to obtain its antecedent parts parameters. …”
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LSSVM parameters tuning with enhanced artificial bee colony by Mustaffa, Zuriani, Yusof, Yuhanis

“…To guarantee its convincing performance, it is crucial to select an appropriate technique in order to obtain the optimized hyper-parameters of LSSVM algorithm.In this paper, an Enhanced Artificial Bee Colony (eABC) is used to obtain the ideal value of LSSVM’s hyper parameters, which are regularization parameter, γ and kernel parameter, σ2.Later, LSSVM is used as the prediction model. …”
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Artificial bee colony in optimizing process parameters of surface roughness in end milling and abrasive waterjet machining by Norfadzlan, Bin Yusup

“…Optimizing the process parameters is essential in order to provide a better quality and economics machining. This research develops an optimization algorithm using artificial bee colony (ABC) algorithm to optimize the process parameters that will lead to minimum surface roughness (Ra) value for both end miling and abrasive waterjet machining. …”
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Time series predictive analysis based on hybridization of meta-heuristic algorithms by Zuriani, Mustaffa, M. H., Sulaiman, Rohidin, Dede, Ernawan, Ferda, Shahreen, Kasim

“…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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Lévy mutation in artificial bee colony algorithm for gasoline price prediction by Mustaffa, Zuriani, Yusof, Yuhanis

“…In this paper, a mutation strategy that is based on Lévy Probabily Distribution is introduced in Artificial Bee Colony algorithm. The purpose is to better exploit promising solutions found by the bees.Such an approach is used to improve the performance of the original ABC in optimizing Least Squares Support Vector Machine hyper parameters.From the conducted experiment, the proposed lvABC shows encouraging results in optimizing parameters of interest.The proposed.lvABC-LSSVM has outperformed existing prediction model, Backpropogation Neural Network (BPNN), in predicting gasoline price.…”
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Estimation of optimal machining control parameters using artificial bee colony by Norfadzlan, Yusup, Arezoo, Sarkheyli, Azlan, Mohd Zain, Siti Zaiton, Mohd Hashim, Norafida, Ithnin

“…This research employed ABC algorithm to optimize the machining control parameters that lead to a minimum surface roughness (R a) value for AWJ machining. …”
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Optimal variational mode decomposition and integrated extreme learning machine for network traffic prediction by Jinmei Shi, Yu-Beng Leau, Kun Li, Huandong Chen

“…Given this context, this paper proposes a network traffic prediction mechanism based on optimized Variational Mode Decomposition (VMD) and Integrated Extreme Learning Machine (ELM). 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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An improved dynamic load balancing for virtualmachines in cloud computing using hybrid bat and bee colony algorithms by Ullah, Arif

“…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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Home buyer assistant using artificial bee colony algorithm / Muhammad Izzat Azri Azman by Azman, Muhammad Izzat Azri

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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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