Search Results - (( simulation optimisation based algorithm ) OR ( using function _ algorithm ))

Single-Solution Simulated Kalman Filter Algorithm for Global Optimisation Problems by Nor Hidayati, Abdul Aziz, Zuwairie, Ibrahim, Nor Azlina, Ab. Aziz, Mohd Saberi, Mohamad, Watada, Junzo

“…The proposed ssSKF algorithm is tested using the 30 benchmark functions of CEC 2014, and its performance is compared to the original SKF algorithm, Black Hole (BH) algorithm, Particle Swarm Optimisation (PSO) algorithm, Grey Wolf Optimiser (GWO) algorithm, and Genetic Algorithm (GA). …”
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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.

“…The proposed ssSKF algorithm is tested using the 30 benchmark functions of CEC 2014, and its performance is compared to that of the original SKF algorithm, Black Hole (BH) algorithm, Particle Swarm Optimisation (PSO) algorithm, Grey Wolf Optimiser (GWO) algorithm and Genetic Algorithm (GA). …”
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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.

“…The proposed ssSKF algorithm is tested using the 30 benchmark functions of CEC 2014, and its performance is compared to that of the original SKF algorithm, Black Hole (BH) algorithm, Particle Swarm Optimisation (PSO) algorithm, Grey Wolf Optimiser (GWO) algorithm and Genetic Algorithm (GA). …”
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Firefly analytical hierarchy algorithm for optimal allocation and sizing of distributed generation in radial distribution network by Bujal, Noor Ropidah

“…Finally, an AHP was integrated with FA to form Firefly Analytical Hierarchy Algorithm (FAHA) to automatically calculate the weight of each objective function based on the load flow outputs followed by the optimisation process. …”
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Optimised intelligent tilt controller scheme using genetic algorithms by Zamzuri, Hairi, Zolotas, Argyrios, Goodall, Roger

“…This paper presents work on a fuzzy control design for improving the performance of tilting trains with local-per vehicle control, i.e. without employing precedence control.An optimisation procedure using Genetic Algorithms as employed to determine both the best fuzzy output membership function and best PID controller parameters. …”
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Tiki-taka algorithm: a novel metaheuristic inspired by football playing style by Mohd Fadzil Faisae, Ab Rashid

“…Purpose Metaheuristic algorithms have been commonly used as an optimisation tool in various fields. …”
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Locust- inspired meta-heuristic algorithm for optimising cloud computing performance by Fadhil, Mohammed Alaa

“…The proposed algorithm is evaluated using the WorkflowSim simulation with a real dataset. …”
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Optimization of multi-agent traffic network system with Q-Learning-Tune fitness function by Tan, Min Keng

“…However, the evaluation function used in the AI is developed based on historical traffic data. …”
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Selective harmonic elimination in multilevel inverter using hybrid APSO algorithm by Memon, Mudasir Ahmed, Mekhilef, Saad, Mubin, Marizan

“…APSO-NR is applied to the seven-level inverter to eliminate fifth and seventh harmonics. In simulations, the performance of the proposed algorithm is compared with genetic algorithm, bee algorithm and particle swarm optimisation. …”
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Meta-heuristic approaches for reservoir optimisation operation and investigation of climate change impact at Klang gate dam by Lai, Vivien Mei Yen

“…By preserving the equilibrium between the proposed MHAs and reservoir risk analysis indices, the stakeholder can select or control the optimal KGD operation by referring to the summary of findings for the observed period assessments. The Whale Optimisation Algorithm (WOA), Harris Hawks Optimisation (HHO) Algorithm, Lévy Flight WOA (LFWOA) and the Opposition-Based Learning of HHO (OBL-HHO) were proposed to simulate the initial model’s response and optimise the Klang Gate Dam (KGD) release operation with observed inflow, water level (storage), release, and evaporation rate (loss). …”
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Control of exothermic batch process using multivariable genetic algorithm by Min, Keng Tan, Chuo, Helen Sin Ee, Farm, Yan Yan, Heng, Jin Tham, Teo, Kenneth Tze Kin

“…GA exploits the probabilistic search method to optimise the specific objective function based on the evolutionary principle. …”
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Role of optimization algorithms based fuzzy controller in achieving induction motor performance enhancement by Hannan M.A., Ali J.A., Hossain Lipu M.S., Mohamed A., Ker P.J., Indra Mahlia T.M., Mansor M., Hussain A., Muttaqi K.M., Dong Z.Y.

Development of a scalable video compression algorithm by Khalifa, Othman Omran, Issa, Sinzobakwira, Olanweraju, Rashidah Funke, Al Khazmi, El Mahdi A

“…The result shows that the managed complexity algorithm based on Lagrangian Multiplier function outperforms the normal encoder. …”
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Optimised multi-robot path planning via smooth trajectory generation by Loke, Zhi Yu

“…A MPSO algorithm, without path smoothening, is used for comparison. …”
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Particle Swarm Optimised Controller for Solid-State Transfer Switch Towards Fast Power Transfer and PQ Mitigation by Sebastian G., Hannan M.A., Al-Shetwi A.Q., Ker P.J., Muttaqi K.M., Uddin M.N.

Dynamic modelling of a single link flexible manipulator in vertical motion using swarm and genetic optimisation by Md. Zain, B. A., Tokhi, M. Osman, Toha, Siti Fauziah

“…In this research, particle swann optimisation (PSO) and genetic algorithm (GA) are used to model a single-link flexible manipulator. …”
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Sensorless Adaptive Fuzzy Logic Control Of Permanent Magnet Synchronous Motor by Hafz Nour, Mutasim Ibrahim

“…The output signal of the PI controller is added to the direct FLC output to compensate any deviations in the motor speed from the reference speed due to parameters variation and disturbances in the load. The design and optimisation of the FLC are carried out using an adaptive fuzzy inference system network that uses the backpropagation, least square and gradient algorithms. …”
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A simulation based fly optimisation algorithm for swarms of mini autonomous surface vehicles application by Zainal Abidin, Zulkifli

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A new optimisation framework based on Monte Carlo embedded hybrid variant mean–variance mapping considering uncertainties by Norhafidzah, Mohd Saad, Muhamad Zahim, Sujod, Mohd Ikhwan, Muhammad Ridzuan, Mohammad Fadhil, Abas, Mohd Shawal, Jadin, Mohd Fadzil, Abdul Kadir

“…The Monte Carlo-embedded MVMO-SH was then used to optimise PVDG in the urban RDN. Simulations were run for several scenarios in three load cases based on 288 segments: residential, commercial, and industrial urban loads. …”
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Performance Comparison of FA, PSO and CS application in SINR Optimisation for LCMV Beamforming Technique by Doroody C., Kiong T.S.