Search Results - (( simulation optimization modified algorithm ) OR ( parameter simulation modified algorithm ))
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Hybrid meta-heuristic algorithm for solving multi-objective aggregate production planning in fuzzy environment
Published 2017“…During the course of the present work, two fuzzy methods (modified Zimmermanns approach and modified angelovs approach ) and fourmeta-heuristics and hybrid meta heuristics including; simulated annealing (SA), modified simulated annealing (MSA), hybrid modified simulated annealing and simplex downhill (MSASD), hybrid modified simulated annealing and modified particle swarm optimization (MSAPSO) were proposed. …”
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Thesis -
2
Dynamic obstacle handling in multi-robot coverage
Published 2024“…The impacts of the modified algorithm’s parameters on simulation results were also studied to determine the optimal parameters for achieving better performance. …”
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1D Multigrid Solver For Finite Element Method
Published 2022“…The new algorithm also has been tested using time simulation. …”
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Monograph -
4
Optimal power flow using the Jaya algorithm
Published 2016“…Simulations are carried out on the modified IEEE 30-bus and IEEE 118-bus networks to determine the effectiveness of the Jaya algorithm. …”
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5
Modified firefly algorithm for directional overcurrent relay coordination in power system protection / Muhamad Hatta Hussain
Published 2020“…The objectives of the studies are to develop a new optimization technique termed as Modified Firefly Algorithm (MFA) for minimizing the relay operating time, to develop a Multi-Objective Modified Firefly Algorithm (MOMFA) for minimizing both the total relay operating time and relay coordination time and to develop an integrated optimal predictor termed as Modified Firefly Algorithm-Artificial Neural Network (MFA-ANN) for accurate prediction of relay operating time. …”
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A harmony search-based learning algorithm for epileptic seizure prediction
Published 2016“…Simulation results show that the proposed algorithm outperforms other metaheuristic algorithms in terms of sensitivity.…”
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Simultaneous computation of model order and parameter estimation for ARX model based on single swarm and multi swarm simulated Kalman filter
Published 2017“…Motivated by the estimation capability of Kalman filter, a new meta-heuristic optimization algorithm known as Simulated Kalman Filter (SKF) has been introduced recently. …”
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9
Development of optimization Alghorithm for uncertain non-linear dynamical system
Published 2004“…An algorithm that definitely can satisfy the objectives is the Dynamic Integrated Systems Optimization and Parameter Estimation (DISOPE) algorithm. …”
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Monograph -
10
Comparison of DC motor position control simulation using MABSA-FLC and PSO-FLC
Published 2019“…This paper explained about the standard fuzzy logic controller that will be compared in terms of performance for simulation with a modified adaptive bats sonar algorithm (MABSA) and also a particle swarm optimization (PSO) algorithm. …”
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Conference or Workshop Item -
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Optimisation of automatic generation control performance in two-area power system with pid controllers using mepso / Lu Li
Published 2018“…The AGC in two-area power system was constructed and simulated by using MATLAB R2017b software. From the simulation results, it was found that with the same number of PID controllers, the performance of AGC optimised by using MEPSO-TVAC algorithm is better in terms of overshoot and fitness value than using EPSO and PSO algorithms. …”
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Thesis -
13
Intelligent Optimization Techniques for Optimal Power Flow using Interline Power Flow Controller
Published 2010“…The optimal control parameters are derived to minimize the transmission line losses employing three intelligent optimization techniques, namely Particle Swarm Optimization (PSO), Genetic Algorithm and Simulated Annealing. …”
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Conference or Workshop Item -
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Fuzzy clustering method and evaluation based on multi criteria decision making technique
Published 2018“…The new proposed method (MBPSO+MKN+GK) Gustafson- Kessel algorithm (GK)integrated with modified of Kohonen Network algorithm (MKN)and modified binary particle swarm optimization (MBPSO) was used to classify the credit scoring data. …”
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Thesis -
15
INTELLIGENT OPTIMIZATION OF INTERLINE POWER FLOW CONTROLLER IN TRANSMISSION SYSTEM
Published 2010“…The optimal parameters are derived to minimize the transmission line losses using three intelligent optimization techniques, namely Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Simulated Annealing (SA). …”
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Thesis -
16
A Method For Solving Mult-Objective Optimization Problem: Vector Evaluated Genetic Algorithm (Vega)
Published 2009“…Consequently, some components of GAs had been modified to produce Vector Evaluated Genetic Algorithm (VEGA) in order to adapt the nature of MOOP. …”
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Final Year Project Report / IMRAD -
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An optimized aggregate marker algorithm for bandwidth fairness improvement in classifying traffic networks
Published 2016“…The marking probability mechanism was also studied to check how parameters in the traffic rate affect fairness. Extensive simulations were carried out to implement the algorithm using the NS2 simulator and compare the proposed marker algorithm with several other algorithms. …”
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Application of Evolutionary Algorithm for Assisted History Matching
Published 2014“…When the differences between the observed performance data and simulated data are found, the iterations are made to modify the accuracy of the match. …”
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Final Year Project -
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Parameter estimation of multicomponent transient signals using deconvolution and ARMA modelling techniques
Published 2003“…This approach also provides a graphical procedure for detecting and validating the number of exponential signals present in the data. Some computer simulation results are presented to justify the need for this modified method of analysis. …”
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Fast and optimal tuning of fractional order PID controller for AVR system based on memorizable-smoothed functional algorithm
Published 2022“…Therefore, this study proposes a modified smoothed function algorithm (MSFA) based method to tune the FOPID controller of AVR system since it requires fewer number of function evaluation per iteration. …”
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