Search Results - (( dynamic optimization based algorithm ) OR ( using evolutionary optimization algorithm ))

Dynamic social behavior algorithm for real-parameter optimization problems and optimization of hyper beamforming of linear antenna arrays by Prajindra�Sankar K., Kiong T.S., Siaw�Paw J.K.

A Multi-objective Evolutionary Algorithm Based On Decomposition For Continuous Optimization Using A Step-function Technique by Chuah, How Siang

“…One of the recent MOEA/D algorithms, i.e., Constant-distance based Neighbours for MOEA/D with Dynamic Weight Vector Adjustment (MOEA/D-AWACD), integrates the concept of a constant-distance neighbourhood and a dynamic weight vector design. …”
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Using the evolutionary mating algorithm for optimizing the user comfort and energy consumption in smart building by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

“…EMA belongs to the evolutionary computation group of nature-inspired metaheuristic algorithms and offers a promising solution. A comparative analysis is conducted with other well-known algorithms such as Particle Swarm Optimization (PSO), Differential Evolution (DE), Ant Colony Optimization (ACO), Biogeography-Based Optimization (BBO), Teaching-Learning Based Optimization (TLBO), and Beluga Whale Optimization (BWO). …”
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Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain by Mohamad Zihin , Mohd Zain

“…BSA gave the best overall performance by showing improved solutions and more robust convergence in comparison with various metaheuristics used in this work. Multi-objective optimization problems are also addressed by proposing a modified multi-criterion optimization algorithm based on a Pareto-based Particle Swarm Optimization (PSO) algorithm called Multi-Objective Particle Swarm Optimization (MOPSO). …”
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Implementation and analysis of BBO algorithm for better damping of rotor oscillations of a synchronous machine by Kasilingam G., Pasupuleti J., Nithiyananthan K.

“…Circuit oscillations; Evolutionary algorithms; Heuristic algorithms; Information systems; Information use; MATLAB; Optimization; Synchronous machinery; System stability; Systems analysis; Two term control systems; Biogeographybased optimizations (BBO); Dynamic performance; Electromechanical oscilla-tions; Integral Square Error (ISE); Power system stability; Power system stabilizer (PSS); Proportional integral derivative controllers; Single machine infinite bus system; Proportional control systems…”

Investigation on the dynamic of computation of semi autonomous evolutionary computation for syntactic optimization of a set of programming codes by Mohammad Sigit Arifianto, Tze, Kenneth Kin Teo, Liau, Chung Fan, Liawas Barukang, Zaturrawiah Ali Omar

“…In order to have a realistic characteristic of a parallel computing engine, a Rocks based computer cluster was built and used for the test. Genetic Algorithm as one of the Evolutionary Computation method improve the execution of parallel programming codes by optimizing the number of processors and the distribution of data. …”
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A multi-objective particle swarm optimization algorithm based on dynamic boundary search for constrained optimization by Mohd Zain, Mohamad Zihin, Kanesan, Jeevan, Chuah, Joon Huang, Dhanapal, Saroja, Kendall, Graham

“…M-MOPSO is compared with four other algorithms namely, MOPSO, Multi-Objective Grey Wolf Optimizer (MOGWO), Multi-Objective Evolutionary Algorithm based on Decompositions (MOEA/D) and Multi-Objective Differential Evolution (MODE). …”
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Pneumatic servo position control optimization using adaptive-domain prescribed performance control with evolutionary mating algorithm by Addie Irawan, Hashim, Mohd Herwan, Sulaiman, Mohd Syakirin, Ramli, Mohd Iskandar Putra, Azahar

“…Therefore, this study presents an optimal control strategy using Adaptive Domain Prescribed Performance Control (AD-PPC) cascaded with PID and optimized using the Evolutionary Mating Algorithm (EMA) for a pneumatic servo system (PSS). …”
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A novel clustering based genetic algorithm for route optimization by Aibinu, Abiodun Musa, Salau, Habeeb Bello, Najeeb, Athaur Rahman, Nwohu, Mark Ndubuka, Akachukwu, Chichebe

“…It was also observed that the introduction of clustering based selection algorithm guaranteed the selection of cluster with the optimal solution in every generation. …”
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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.

Evolutionary Multiobjective optimization for automatic generation Of Neural game controller by Chin, Kim On, Yong, Yung Nan

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Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms by Koh, Johnny Siaw Paw

“…This thesis presents a new approach to optimize the performance of a dual beam optical scanning system in terms of its scanning combinations and speed, using Genetic Algorithm (GA). …”
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Implementation of Evolutionary Algorithms to Parametric Identification of Gradient Flexible Plate Structure by Annisa, Jamali, Muhammad Hasbollah, Hassan, Lidyana, Roslan, Muhamad Sukri, Hadi

“…This paper focused on modelling of a gradient flexible plate system utilizing an evolutionary algorithm, namely particle swarm optimization (PSO) and cuckoo search (CS) algorithm. …”
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Implementation of Evolutionary Algorithms to Parametric Identification of Gradient Flexible Plate Structure by Annisa, Jamali, Lidyana, Roslan, Muhammad Hasbollah, Hassan

“…This paper focused on modelling of a gradient flexible plate system utilizing an evolutionary algorithm, namely particle swarm optimization (PSO) and cuckoo search (CS) algorithm. …”
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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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Improvement and application of particle swarm optimization algorithm by Deevi, Durga Praveen, Kodadi, Sharadha, Allur, Naga Sushma, Dondapati, Koteswararao, Chetlapalli, Himabindu, Perumal, Thinagaran

“…This method combines CPTD with the Genetic Algorithm and PSO (GAPSO), resulting in an effective strategy for dynamic formation reconfiguration and path optimization. …”
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Nonlinear auto-regressive model structure selection using binary particle swarm optimization algorithm / Ahmad Ihsan Mohd Yassin by Mohd Yassin, Ahmad Ihsan

“…A MySQL database was created to analyze the optimization results and speed up computations of the optimization algorithm. …”
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An integrated reservoir modelling and evolutionary algorithm for optimizing field development in a mature fractured reservoir by Sambo, C.H., Hematpour, H., Danaei, S., Herman, M., Ghosh, D.P., Abass, A., Elraies, K.A.

“…The second method is automatic optimization using Genetic Algorithm. That depends on the principle of natural selection as proposed by Darwin The genetic program was coupled with the reservoir flow model to re-evaluate the chosen wells at each iteration until obtaining the optimal choice. …”
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Application of system identification method coupled with evolutionary algorithms for the optimization of power consumption in a pem fuel cell propulsion system / Suhadiyana Hanapi by Hanapi, Suhadiyana

“…This thesis makes a number of key contributions to the advancement of fuel cell vehicle design within two main research areas; powertrain system design based on quality energy, and optimization system based on biology based algorithms. …”
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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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