Search Results - (( a distribution using algorithm ) OR ( parameter adaptation swarm algorithm ))

An Adaptive Switching Cooperative Source Searching And Tracing Algorithms For Underwater Acoustic Source Localization by Majid, Mad Helmi Ab.

“…Firstly, to detect the source, a Source Detection Algorithm (SDA) known as a Distributed Lévy Flight (DLF) is proposed. …”
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Accuracy enhancement for zone mapping of a solar radiation forecasting based multi-objective model for better management of the generation of renewable energy by Ehteram M., Ahmed A.N., Fai C.M., Afan H.A., El-Shafie A.

“…Air quality; Decision making; Forecasting; Fuzzy inference; Fuzzy neural networks; Fuzzy systems; Genetic algorithms; Inference engines; Mapping; Mean square error; Multiobjective optimization; Optimal systems; Particle swarm optimization (PSO); Quality control; Renewable energy resources; Solar radiation; Uncertainty analysis; Adaptive neuro-fuzzy inference system; ANFIS; Multi objective algorithm; Multi objective particle swarm optimization; Multi-objective genetic algorithm; Renewable energies; Renewable energy generation; Solar radiation forecasting; Parameter estimation…”

A Modified Particle Swarm Optimization for Efficient Maximum Power Point Tracking Under Partial Shading Condition by Koh J.S., Tan R.H.G., Lim W.H., Tan N.M.L.

“…Therefore, a modified PSO hybridized with adaptive local search (MPSO-HALS) is designed as a robust, real-time MPPT algorithm. …”

Optimal allocation and sizing of capacitor bank and distributed generation using particle swarm optimization by El Tawil, Naji Ammar Mansour

“…The PSO algorithm allocates and determines the size of the capacitor and distributed generation in the power system. …”
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Single-solution Simulated Kalman Filter algorithm for global optimisation problems by Abdul Aziz, N.H., Ibrahim, Z., Ab Aziz, N.A., Mohamad, M.S., Watada, J.

“…In the proposed ssSKF algorithm, the initialisation parameters are not constants, but they are produced by random numbers taken from a normal distribution in the range of 0, 1, thus excluding them from tuning requirement. …”
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Single-solution Simulated Kalman Filter algorithm for global optimisation problems by Abdul Aziz, N.H., Ibrahim, Z., Ab Aziz, N.A., Mohamad, M.S., Watada, J.

“…In the proposed ssSKF algorithm, the initialisation parameters are not constants, but they are produced by random numbers taken from a normal distribution in the range of 0, 1, thus excluding them from tuning requirement. …”
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Enhanced segment particle swarm optimization for large-scale kinetic parameter estimation of escherichia coli network model by Mohammed Adam, Kunna Azrag

“…In this regard, a Local Sensitivity Analysis, Segment Particle Swarm Optimization (Se-PSO) algorithm, and the Enhanced Segment Particle Swarm Optimization (ESe-PSO) algorithm was adapted and proposed to estimate the parameters. …”
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Fitness-guided particle swarm optimization with adaptive Newton-Raphson for photovoltaic model parameter estimation by Premkumar M., Ravichandran S., Hashim T.J.T., Sin T.C., Abbassi R.

“…This study introduces a new approach for parameter optimization in the four-diode photovoltaic (PV) model, employing a Dynamic Fitness-Guided Particle Swarm Optimization (DFGPSO) algorithm and Enhanced Newton-Raphson (ENR) method. …”

A memory-guided Jaya algorithm to solve multi-objective optimal power flow integrating renewable energy sources by Ahmadipour M., Ali Z., Ramachandaramurthy V.K., Ridha H.M.

Multi agent quality of service routing based on scheme ant colony optimization algorithm by Baygi, Maassoumeh Javadi

“…In saturated load, efficiency is a very important parameter and a few changes in it can result in high performance of network to delivery of data.…”
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Nature-inspired parameter controllers for ACO-based reactive search by Sagban, Rafid, Ku-Mahamud, Ku Ruhana, Abu Bakar, Muhamad Shahbani

“…This study proposes machine learning strategies to control the parameter adaptation in ant colony optimization algorithm, the prominent swarm intelligence metaheuristic.The sensitivity to parameters’ selection is one of the main limitations within the swarm intelligence algorithms when solving combinatorial problems.These parameters are often tuned manually by algorithm experts to a set that seems to work well for the problem under study, a standard set from the literature or using off-line parameter tuning procedures. …”
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Design-point performance adaptation of small gas turbine using particle swarm optimization by Machmudah, A., Lemma, T.A.

“…Target parameters are shaft power, fuel flow, turbine exit temperature, turbine exit pressure, and thermal efficiency with seven adapted parameters as the optimization parameters. …”
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Design-point performance adaptation of small gas turbine using particle swarm optimization by Machmudah, A., Lemma, T.A.

“…Target parameters are shaft power, fuel flow, turbine exit temperature, turbine exit pressure, and thermal efficiency with seven adapted parameters as the optimization parameters. …”
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Forecasting Solar Power Using Hybrid Firefly and Particle Swarm Optimization (HFPSO) for Optimizing the Parameters in a Wavelet Transform-Adaptive Neuro Fuzzy Inference System (WT-... by Abdullah, Nor Azliana, Rahim, Nasrudin Abd, Gan, Chin Kim, Nor Adzman, Noriah

“…The HFPSO is the hybridization of the firefly (FF) and particle swarm optimization (PSO) algorithm, which is employed in optimizing the premise parameters of the ANFIS to increase the accuracy of the model. …”
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Forecasting Solar Power Using Hybrid Firefly And Particle Swarm Optimization (HFPSO) For Optimizing The Parameters In A Wavelet Transform-Adaptive Neuro Fuzzy Inference System (WT-... by Abd Rahim, Nasrudin, Gan, Chin Kim, Abdullah, Nor Azliana, Adzman, Noriah Nor

“…The HFPSO is the hybridization of the firefly (FF) and particle swarm optimization (PSO) algorithm, which is employed in optimizing the premise parameters of the ANFIS to increase the accuracy of the model. …”
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Performance Analysis of Active Power Filter for Harmonic Compensation using PI-PSO by Thajeel, Ekhlas Mhawi, Hamdan, Daniyal, M. H., Sulaiman

“…The simulated system is a three phase balanced voltage system with nonlinear load .A particle swarm optimization (PSO) is implemented to optimize the gains of a proportional-integral (PI) algorithm to control the SAPF. …”
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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

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Particle swarm optimization-based model-free adaptive control for time-varying batch processes by Wang, Zhao, A.S., Sadun, N.A., Jalaludin, J., Jalani, S.N.H., Arifin, Mohamed Sunar, N., Muhammad Ashraf, Fauzi

“…Further, considering that the adopted model-free adaptive control involves seven control parameters, such as cognitive scaling factor (φ1), social scaling factor (φ2), inertia weight (φ3), learning rate (η), control parameter update rate, exploration rate and learning rate for MFAC obtained by a particle swarm optimization (PSO) algorithm in combination with a criterion function performance index. …”
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Fuzzy Adaptive Tuning of a Particle Swarm Optimization Algorithm for Variable-Strength Combinatorial Test Suite Generation by Kamal Z., Zamli, Ahmed, Bestoun S., Mahmoud, Thair, Afzal, Wasif

“…Research has shown that stochastic population-based algorithms such as particle swarm optimization (PSO) can be efficient compared to alternatives for VS-CIT problems. …”
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A Navigation Strategy for Swarm Robotics Based on Bat Algorithm Optimization Technique by Nur Aisyah Syafinaz, Suarin, Pebrianti, Dwi, Bayuaji, Luhur, Muhammad, Syafrullah, Zulkifli, Musa

“…This paper aims to adapt Bat Algorithm (BA) optimization techniques to the swarm robotics system. …”
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