Search Results - (( pattern bees algorithm ) OR ( patterns path algorithm ))

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. …”
Get full text
Get full text
Get full text

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.…”
Get full text
Get full text
Get full text

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. …”
Get full text
Get full text
Get full text

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.…”
Get full text
Get full text

Simulation performance comparison of A*, GLS, RRT and PRM path planning algorithms by Muhammad, Aisha, Nor Rul Hasma, Abdullah, Mohammad A.H., Ali, Shanono, Ibrahim Haruna, Rosdiyana, Samad

“…In this study, four robust path planning algorithms, namely: Probabilistic Roadmaps (PRMs), A-star, the Rapidly Exploring Random Trees (RRTs), and Generalized Laser Simulator (GLS), were simulated and their performance was measured and compared according to the total path distance covered, search time and path smoothness. …”
Get full text
Get full text
Get full text
Get full text

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.…”
Get full text
Get full text
Get full text

A generalized laser simulator algorithm for optimal path planning in constraints environment by Aisha, Muhammad

“…The suggested algorithm outperforms the competition in terms of improving path cost, smoothness, and search time. …”
Get full text

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. …”
Get full text
Get full text
Get full text

Intelligent road recognition system for automous vehicle by Soon, Adrian Bee Toing

Get full text
Get full text
Get full text
Get full text

A Scalable Algorithm for Constructing Frequent Pattern Tree by Noraziah, Ahmad, Herawan, Tutut, Zailani, Abdullah, Mustafa, Mat Deris

“…Frequent Pattern Tree (FP-Tree) is a compact data structure of representing frequent itemsets. …”
Get full text
Get full text
Get full text

ZigBee environment for indoor localization by Chieh K.S., Keong N.Y., Burhan M.F., Balasubramaniam N., Din N.M.

Scheduling of batch process plant / Abdul Aziz Abu Bakar by Abu Bakar, Abdul Aziz

“…Batch production is used throughout the process industries for the manufacture of fine chemical, plastics, pharmaceuticals, paints, ceramics, cosmetics, or whatever production quantities are small, product value is very high or product demand pattern is changeable. This research work is devoted to software development of scheduling and control algorithm of batch process plant using shortest path method developed by Dijkstra and K* shortest path method developed by Jin Y. …”
Get full text
Get full text

Deterministic and stochastic inventory routing problems with backorders using artificial bee colony / Huda Zuhrah Ab Halim by Huda Zuhrah , Ab Halim

“…The inventory holding cost is assumed to be product specific and only incurred at the assembly plant. An Artificial Bee Colony (ABC) algorithm is proposed for the problem. …”
Get full text
Get full text
Get full text

RFID and ZigBee integrated environment for indoor localization by Keong N.Y., Chieh K.S., Burhan M.F., Balasubramaniam N., Din N.M.

Feature extraction: hand shape, hand position and hand trajectory path by Bilal, Sara Mohammed Osman Saleh, Akmeliawati, Rini

Get full text
Get full text
Get full text

Animal voice recognition for identification (ID) detection system by Yeo, Che Yong, Syed Mohamed, Syed Abdul Rahman Al-Haddad, Ng, Chee Kyun

“…In this paper, an animal identification (ID) detection system based on animal voice pattern recognition algorithm has been developed. …”
Get full text
Get full text

Dog voice identification (ID) for detection system by Yeo, Che Yong, Syed Mohamed, Syed Abdul Rahman Al-Haddad, Ng, Chee Kyun

“…In this paper, an animal identification (ID) detection system based on animal voice pattern recognition algorithm has been developed. …”
Get full text
Get full text

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.…”
Get full text
Get full text
Get full text

Optimization of economic lot scheduling problem with backordering and shelf-life considerations using calibrated metaheuristic algorithms by Mohammadi, M., Musa, S.N., Bahreininejad, A.

“…Efficient search procedures are presented to obtain the optimum solutions by employing four well-known metaheuristic algorithms, namely genetic algorithm (GA), particle swarm optimization (PSO), simulated annealing (SA), and artificial bee colony (ABC). …”
Get full text
Get full text
Get full text

Development of behavior-based reactive navigation system for mobile robot by Mohd Hamami, Mohd Ghazali

“…The repeatability tests shown that the developed navigation algorithm able the robot to reach the target with the similar navigation path pattern outcome in each simulation tests. …”
Get full text
Get full text