Search Results - (( evolution classification based algorithm ) OR ( using evolutionary bees algorithm ))

Congestion management based optimization technique using bee colony by Rahim M.A., Musirin I., Abidin I.Z., Othman M.M., Joshi D.

“…Tests conducted on the IEEE 30-Bus Reliability Test System for performance assessment revealed that the proposed bee algorithm technique is better than evolutionary programming technique in addressing this problem. �2010 IEEE.…”

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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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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Neural network training using hybrid particle-move artificial bee colony algorithm for pattern classification by Al Nuaimi, Zakaria Noor Aldeen Mahmood, Abdullah, Rosni

“…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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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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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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Improving the modeling capacity of Volterra model using evolutionary computing methods based on Kalman Smoother adaptive filter by ., Edwar Yazid, Mohd Shahir Liew, Setyamartana Parman, Velluruzhati

“…The first step is combining the forward and backward estimator in the original Volterra model; the second step is reformulating the Volterra model into a state-space model so that the Kalman Smoother (KS) adaptive filter can be used to estimate the kernel coefficients; the third step is optimization of KS parameters using evolutionary computing algorithms such as particle swarm optimization (PSO), genetic algorithm (GA) and artificial bee colony (ABC). …”
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System performances analysis of reservoir optimization�simulation model in application of artificial bee colony algorithm by Hossain M.S., El-Shafie A., Mahzabin M.S., Zawawi M.H.

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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Comparative analysis of spiral dynamic algorithm and artificial bee colony optimization for position control of flexible link manipulators by Nor Maniha, Abdul Ghani, Nizaruddin, M. Nasir, Azrul Azim, Abdullah Hashim

“…Interestingly, the manipulator's behaviours using the spiral dynamics algorithm for PID controller tuning were superior to those using alternative methods. …”
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Improving the modeling capacity of Volterra model using evolutionary computing methods based on Kalman smoother adaptive filter by Yazid, E., Liew, M.S., Parman, S., Kurian, V.J.

“…The first step is combining the forward and backward estimator in the original Volterra model; the second step is reformulating the Volterra model into a state-space model so that the Kalman Smoother (KS) adaptive filter can be used to estimate the kernel coefficients; the third step is optimization of KS parameters using evolutionary computing algorithms such as particle swarm optimization (PSO), genetic algorithm (GA) and artificial bee colony (ABC). …”
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Performance Analyses of Nature-inspired Algorithms on the Traveling Salesman’s Problems for Strategic Management by Julius, Beneoluchi Odili, M. N. M., Kahar, Noraziah, Ahmad, M., Zarina, Riaz, Ul Haq

“…After critical assessments of the performances of eleven algorithms consisting of two heuristics (Randomized Insertion Algorithm and the Honey Bee Mating Optimization for the Travelling Salesman’s Problem), two trajectory algorithms (Simulated Annealing and Evolutionary Simulated Annealing) and seven population-based optimization algorithms (Genetic Algorithm, Artificial Bee Colony, African Buffalo Optimization, Bat Algorithm, Particle Swarm Optimization, Ant Colony Optimization and Firefly Algorithm) in solving the 60 popular and complex benchmark symmetric Travelling Salesman’s optimization problems out of the total 118 as well as all the 18 asymmetric Travelling Salesman’s Problems test cases available in TSPLIB91. …”
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Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain by Mohamad Zihin , Mohd Zain

“…Two multi-objective fed-batch models are also used as case studies to verify the performance of the proposed algorithm. …”
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Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets by Saeed, Sana

“…The proposed algorithm is grounded on the two famous metaheuristic algorithms: cuckoo search (CS) and covariance matrix adaptation evolution strategy (CMA-es). …”
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Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals by Too, Jing Wei

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Algorithmic design issues in adaptive differential evolution schemes: Review and taxonomy by Al-Dabbagh, Rawaa Dawoud, Neri, Ferrante, Idris, Norisma, Baba, Mohd Sapiyan

“…These fine-tuning techniques continue to be the object of ongoing research. Differential evolution (DE) is a simple yet powerful population-based metaheuristic. …”
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Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

“…Evolutionary computation is the name given to a collection of algorithms based on the evolution of a population toward a solution of a certain problem. …”
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Feature selection optimization using hybrid relief-f with self-adaptive differential evolution by Zainudin, Muhammad Noorazlan Shah, Sulaiman, Md. Nasir, Mustapha, Norwati, Perumal, Thinagaran, Ahmad Nazri, Azree Shahrel, Mohamed, Raihani, Abd Manaf, Syaifulnizam

“…Hence, feature selection is embedded to select the most meaningful features based on their rank. Differential evolution (DE) is one of the evolutionary algorithms that are widely used in various classification domains. …”
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Genetic ensemble biased ARTMAP method of ECG-Based emotion classification by Loo, C.K., Liew, W.S., Sayeed, M.S.

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Effective EEG channels for emotion identification over the brain regions using differential evolution algorithm by Al-Qazzaz, Noor Kamal, Sabir, Mohannad K., Md. Ali, Sawal Hamid, Ahmad, Siti Anom, Grammer, Karl

“…The spectral features were performed by employing the relative spectral powers of delta (δRP), theta (θRP), alpha (αRP), beta (βRP), and gamma (γRP). The differential evolution-based channel selection algorithm (DEFS_Ch) was computed to find the most suitable EEG channels that have the greatest efficacy for identifying the various emotional states of the brain regions. …”
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