Search Results - pattern ((means algorithm) OR (bees algorithm))

Optimization Of Pid Controller For Double-Link Flexible Robotic Manipulator Using Metaheuristic Algorithms by Annisa, Jamali, Intan Zaurah, Mat Darus, Hanim, Mohd Yatim, Mat Hussin, Ab Talib

“…This paper investigates the optimization approach of PID controller for double-link flexible robotic manipulator using metaheuristic algorithm. This research focus on population-based metaheuristic that is particle swarm optimization (PSO) and artificial bees algorithm (ABC) to tune the PID control parameters of the system. …”
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Neural Network Training Using Hybrid Particle-move Artificial Bee Colony Algorithm for Pattern Classification by Nuaimi, Zakaria Noor Aldeen Mahmood Al, Abdullah, Rosni

“…Artificial Bees Colony (ABC) optimization algorithm is one of the competitive algorithms in the SI algorithms group. …”
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Neural network training using hybrid particle-move artificial bee colony algorithm for pattern classification by Al Nuaimi, Zakaria Noor Aldeen Mahmood, Abdullah, Rosni

“…In this work, we aimed to highlight the performance of the Hybrid Particle-move Artificial Bee Colony (HPABC) algorithm by applying it on the ANNT application.The performance of the HPABC algorithm was investigated on four benchmark pattern-classification data sets and the results were compared with other algorithms.The results obtained illustrate that HPABC algorithm can efficiently be used for ANNT.HPABC outperformed the original ABC and PSO as well as other state-of-art and hybrid algorithms in terms of time, function evaluation number and recognition accuracy.…”
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Application of the bees algorithm to the selection features for manufacturing data by Pham, D.T, Mahmuddin, Massudi, Otri, S., Al-Jabbouli, H.

“…The Bees Algorithm is employed to select an optimal set of features for a particular pattern classification task. …”
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Prediction of Rainfall Trends using Mahalanobis-Taguchi System by Jamil M.A.M., Abu M.Y., Zaini S.N.A.M., Aris N.H., Pinueh N.S., Jaafar N.N., Muhammad W.Z.A.W., Ramlie F., Harudin N., Sari E., Ghani N.A.A.A.

“…Finally, the validation with T mean-based error (Tmbe) using Mean Absolute Error (MAE) revealed a pattern of errors to provide insight to find the significant parameters of MTS. ? …”

Prediction of rainfall trends using Mahalanobis-Taguchi system by Muhammad Arieffuddin, Mohd Jamil, Mohd Yazid, Abu, Sri Nur Areena, Mohd Zaini, Nurul Haziyani, Aris, Nur Syafikah, Pinueh, Nur Najmiyah, Jaafar, Wan Zuki Azman, Wan Muhammad, Faizir, Ramlie, Nolia, Harudin, Emelia Sari, ., Nadiatul Adilah, Ahmad Abdul Ghani

“…Finally, the validation with T mean-based error (Tmbe) using Mean Absolute Error (MAE) revealed a pattern of errors to provide insight to find the significant parameters of MTS.…”
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Artificial Bee Colony With Differential Evolution Algorithm For Feature Extraction And Selection Of Mass Spectrometry Data by Mohamed Yusoff, Syarifah Adilah

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Clustering natural language morphemes from EEG signals using the Artificial Bee Colony algorithm by Sulaiman, Suriani, Ahmed Yahya, Saba, Mohd Shukor, Nur Sakinah, Ismail , Amelia Ritahani, Zaahirah, Qazi, Yaacob, Hamwira, Abdul Rahman, Abdul Wahab, Dzulkifli, Mariam Adawiah

“…This study aims at analyzing EEG signals for the purpose of clustering natural language morphemes using the Artificial Bee Colony (ABC) algorithm. Using as input the features extracted from EEG signals during morphological priming tasks, our experimental results indicate that applying the ABC algorithm on EEG datasets to cluster Malay morphemes produces promising results.…”
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Clustering natural language morphemes from EEG signals using the Artificial Bee Colony algorithm by Sulaiman, Suriani, Ahmed Yahya, Saba, Mohd Shukor, Nur Sakinah, Ismail , Amelia Ritahani, Zaahirah, Qazi, Yaacob, Hamwira Sakti, Abdul Rahman, Abdul Wahab, Dzulkifli, Mariam Adawiah

“…This study aims at analyzing EEG signals for the purpose of clustering natural language morphemes using the Artificial Bee Colony (ABC) algorithm. Using as input the features extracted from EEG signals during morphological priming tasks, our experimental results indicate that applying the ABC algorithm on EEG datasets to cluster Malay morphemes produces promising results.…”
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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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Intelligent road recognition system for automous vehicle by Soon, Adrian Bee Toing

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Pattern discovery using k-means algorithm by Ahmed, Almahdi Mohammed, Wan Ishak, Wan Hussain, Md Norwawi, Norita, Alkilany, Ahmed

“…This paper will discuss the results of a pattern extraction process using a clustering algorithm that is k-means. …”
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MINING CUSTOMER DATA FOR DECISION MAKING USING NEW HYBRID CLASSIFICATION ALGORITHM by Aurangzeb, khan, Baharum, Baharudin, Khairullah, khan

“…The experimental result shows that the proposed hybrid k-mean plus MFP algorithm can generate more useful pattern from large stock data.…”
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ZigBee environment for indoor localization by Chieh K.S., Keong N.Y., Burhan M.F., Balasubramaniam N., Din N.M.

Fast and Accuracy Control Chart Pattern Recognition using a New cluster-k-Nearest Neighbor by Brahim Belhaouari, samir

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Fast and Accuracy Control Chart Pattern Recognition using a New cluster-k-Nearest Neighbor by Brahim Belhaouari, samir

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Pattern Discovery Using K-Means Algorithm by Ahmed, AM, Norwawi, NM, Ishak, WHW, Alkilany, A

“…This paper will discuss the results of a pattern extraction process using a clustering algorithm that is k-means. …”

MINING CUSTOMER DATA FOR DECISION MAKING USING NEW HYBRID CLASSIFICATION ALGORITHM by Aurangzeb, khan, Baharum, Baharudin, Khairullah, Khan

“…The experimental result shows that the proposed hybrid k-mean plus MFP algorithm can generate more useful pattern from large stock data.…”
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Frequent patterns minning of stock data using hybrid clustering association algorithm by B., Baharudin, A., Khan, K., Khan

“…The experimental result shows that the proposed hybrid k-mean plus MFP algorithm can generate more useful pattern from large stock data. …”
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Pattern Classification of Human Epithelial Images by Mohd Isa, Mohd Fazlie

“…Last but not least, from the mean of properties, it will classify into the pattern after ranging the value of mean properties of each of the pattern itself that has been done in classification stage.…”
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