Search Results - (( global reduction methods algorithm ) OR ( based optimization based algorithm ))*

A firefly algorithm based hybrid method for structural topology optimization by Gebremedhen, H.S., Woldemichael, D.E., Hashim, F.M.

“…In this paper, a firefly algorithm based hybrid algorithm through retaining global convergence of firefly algorithm and ability to generate connected topologies of optimality criteria (OC) method is proposed as an alternative method to solve stress-based topology optimization problems. …”
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Simulated Kalman Filter algorithms for solving optimization problems by Nor Hidayati, Abdul Aziz

“…In this research, two novel estimation-based metaheuristic optimization algorithms, named as Simulated Kalman Filter (SKF), and single-solution Simulated Kalman Filter (ssSKF) algorithms are introduced for global optimization problems. …”
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Optimal power flow using hybrid firefly and particle swarm optimization algorithm by Khan, Abdullah, Hizam, Hashim, Abdul Wahab, Noor Izzri, Othman, Mohammad Lutfi

“…In this paper, a novel, effective meta-heuristic, population-based Hybrid Firefly Particle Swarm Optimization (HFPSO) algorithm is applied to solve different non-linear and convex optimal power flow (OPF) problems. …”
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Network reconfiguration and control for loss reduction using genetic algorithm by Jawad, Mohamed Hassan Izzaldeen

“…The proposed solution to this problem is based on a general combinatorial optimization algorithm known as Genetic Algorithm, and the load flow equations in distribution network. …”
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Optimized scheduling for an airconditioning system based on indoor thermal comfort using the multiobjective improved global particle swarm optimization by Haniff, Mohamad Fadzli, Selamat, Hazlina, Khamis, Nuraqilla, Alimin, Ahmad Jais

“…The main contribution of this paper is a new optimized AC scheduling approach that focuses on indoor thermal comfort using a new multi-objective optimization algorithm, called the improved global particle swarm optimization (IGPSO), which able to find better optimal solutions faster than its original version, the global particle swarm optimization (GPSO) algorithm. …”
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Metaheuristic Algorithm for Wellbore Trajectory Optimization by Biswas, K., Vasant, P.M., Vintaned, J.A.G., Watada, J.

“…From those methods in this study, we have focused on metaheuristic approaches based on PSO (particle swarm optimization) which will be used to optimize wellbore trajectory. …”
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Efficient classifying and indexing for large iris database based on enhanced clustering method by Khalaf, Emad Taha, Mohammed, Muamer N., Kohbalan, Moorthy, Khalaf, Ahmad Taha

“…The proposed method can be used to perform global search and exhibits quick convergence rate while optimizing the initial clustering centers of the K-means algorithm. …”
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New global maximum power point tracking and modular voltage equalizer topology for partially shaded photovoltaic system / Immad Shams by Immad , Shams

“…In terms of controller-based, in this work, a new global maximum power point tracking (GMPPT) algorithm based on a modified butterfly optimization algorithm (MBOA) has been proposed. …”
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Low Complexity Error Correction in Low Density Parity Check (LDPC) Code Decoder and Encoder for Decode and Forward Cooperative Wireless Communication by JAM'AAH, SUUD

“…By using the optimization min-sum belief propagation approach, a low complexity min-sum (MS) based decoding algorithm called Variable Global Optimization Min-Sum (VGOMS) has been developed. …”
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Dual search maximum power point algorithm based on mathematical analysis under partially-shaded conditions by Hajighorbani, Shahrooz

“…In the first group, the conventional techniques are combined with other techniques and the second group is based on the optimization methods. One of the main challenges of MPPT techniques under PSCs is ability of the algorithms to find the GMPP faster with minimal oscillation in power. …”
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Neural network modeling and optimization for spray-drying coconut milk using genetic algorithm and particle swarm optimization by Lee, Jesee Kar Ming

“…Firstly, using MATLAB program, the ANN model is developed based on optimized topology and is then furthered optimized by genetic algorithm (GA) and particle swarm optimization (PSO) using MINITAB program. …”
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Long-term optimal planning for renewable based distributed generators and plug-in electric vehicles parking lots toward higher penetration of green energy technology by ALAhmad A.K., Verayiah R., Shareef H., Ramasamy A.

“…Moreover, to ensure realism, the model incorporates uncertainties related to stochastic variables such as the intermittent nature of RESs, EV energy and time variables, loads, and energy price fluctuations, using Monte Carlo Simulation (MCS) and the backward reduction method (BRM). A hybrid optimization algorithm addresses the proposed objectives, combining the non-dominated sorting genetic algorithm (NSGA-II) and multi-objective particle swarm optimization (MOPSO) to minimize the three distinct objective functions concurrently. …”

A study on model-free approach for liquid slosh suppression based on stochastic approximation by Ahmad, Mohd Ashraf

“…In addition, the performance of the SPSA based methods is compared to the other stochastic optimization based approaches, which also includes the variants of SPSA based method, such as Global SPSA. …”
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Development of cost reduction mathematical model for natural gas transmission network system by Mehrdad, Nikbakht Eliaderany

“…Therefore, the data clearly exhibit that the proposed method provides a solution that was nearer to an optimized network.…”
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Design optimization of a hybrid electric vehicle powertrain by Mangun, Firdause, Mahmoud Idres, Moumen Mohammed, Abdullah, Kassim Abdulrahman,

“…This paper presents an optimization work on hybrid electric vehicle (HEV) powertrain using Genetic Algorithm (GA) method. …”
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Enhanced Multi-Objective Grey Wolf Optimizer with Lévy Flight and Mutation Operators for Feature Selection by Al-Tashi, Q., Shami, T.M., Abdulkadir, S.J., Akhir, E.A.P., Alwadain, A., Alhussain, H., Alqushaibi, A., Rais, H.M.D., Muneer, A., Saad, M.B., Wu, J., Mirjalili, S.

“…To evaluate the classification performance of the selected feature subset, the proposed approach employs a wrapper-based Artificial Neural Network (ANN). The effectiveness of the LMuMOGWO is validated on 12 conventional UCI benchmark datasets and compared with two existing variants of MOGWO, BMOGWO-S (based sigmoid), BMOGWO-V (based tanh) as well as Non-dominated Sorting Genetic Algorithm II (NSGA-II) and Multi-objective Particle Swarm Optimization (BMOPSO). …”
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Personalized one-shot local adaptation federated learning for mortality prediction in multi-center Intensive Care Unit by Deng, Ting

“…After conducting stepwise experiments and comparing with three benchmark methods - a baseline FL method and two PFL approaches in similar optimization scheme - the results shows that POLA not only systematically optimizes its internal outputs but also outperforms the comparison methods. …”
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Optimal planning and design of hybrid renewable energy system for rural healthcare facilities / Olatomiwa Lanre Joseph by Olatomiwa Lanre , Joseph

“…Then, utilization of cost-effective optimization algorithm for optimal sizing of the energy resources and other system components with accurate mathematical models for energy management of the entire hybrid system. …”
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Enhancement of prediction models using a modified feature selection method in energy consumption by Desmira

“…Hence, it is imperative to devise solutions that address the challenge of forecasting and meeting future energy requirements, particularly when employing machine learning algorithms to analyze data. The issue of using machine learning to choose features for projecting global energy consumption has not yielded much effective computational times. …”
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Modeling and Optimization of Tapered Rectangular Thin-walled Columns Subjected to Oblique Loading for Impact Energy Absorption by Siti Aishah, Rusdan, Tarlochan, Faris, Mohamad Rusydi, Mohamad Yasin

“…RS model using quadratic polynomial function is given as equation (1) below. The optimal design is obtained by using the constrained nonlinear multivariable optimization algorithm provided by MATLAB. …”
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