Search Results - (( based validation using algorithm ) OR ( simulation optimization modified algorithm ))
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1
Optimized clustering with modified K-means algorithm
Published 2021“…Besides, some real data sets were examined to validate the proposed algorithm. Empirical evidences based on simulated data sets indicated that the proposed modified k-means algorithm is able to recognise the optimum number of clusters for uncorrelated data sets. …”
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2
A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution
Published 2018“…The proposed algorithm is scrutinized and validated using the modified IEEE 30-bus test system. …”
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3
New random approaches of modified adaptive bats sonar algorithm for reservoir operation optimization problems
Published 2024“…In the fourth phase, the newly developed algorithm undergoes testing on the formulated ROOPs and compared to several contemporary optimizer algorithms. …”
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4
Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification
Published 2007“…Comparisons based on widely used optimization performance indicators along with outcomes from other research are used. …”
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5
Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification
Published 2007“…Comparisons based on widely used optimization performance indicators along with outcomes from other research are used. …”
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6
Resource allocation technique for powerline network using a modified shuffled frog-leaping algorithm
Published 2018“…The solution is numerically validated and verified by simulation-based powerline channel. …”
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7
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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8
Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification
Published 2007“…Comparisons based on widely used optimization performance indicators along with outcomes from other research are used. …”
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9
Discrete-time system identification using genetic algorithm with single parent-based mating technique
Published 2024“…The methodology encompasses data acquisition, GA program development, SPM technique implementation, and simulation using MATLAB. The study simulated single-input-single-output (SISO) models: ARX and NARX. …”
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10
Novel initialization strategy: Optimizing conventional algorithms for global maximum power point tracking
Published 2024“…The major advantages of this approach are eliminating the need to modify the original algorithm, hybridizing with other algorithms, or employing any complex procedures, as in metaheuristic and optimization MPPT algorithms. …”
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11
PID controller adjustment for MA-LFC by using imperialist competitive algorithm
Published 2013“…In this paper a new evolutionary computing method based on Imperialist Competitive Algorithm (ICA) is used for tuning the elements of a PID controller which is applied in a Multi Area Load Frequency Control System (MA-LFC). …”
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12
Efficiency improvement of a standalone photovoltaic system using fuzzy-based maximum power point tracking algorithm
Published 2016“…The MPPT algorithms imply the optimal duty ratio to drive the matching converter for optimal maximum power tracking. …”
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13
Optimization of chemotherapy using metaheuristic optimization algorithms / Prakas Gopal Samy
Published 2024“…Stability and bifurcation analyses illuminate the model's responsiveness to varying control parameters. Empirical validation and performance assessment are conducted through rigorous benchmarking simulations on the PlatEMO platform, covering ten algorithms. …”
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14
Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm
Published 2025“…The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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15
Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm
Published 2025“…The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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16
Mathematical modelling of mass transfer in a multi-stage rotating disc contactor column
Published 2005“…Based on this formulation, a Mass Transfer of A Single Drop (MTASD) Algorithm was designed, followed by a more realistic Mass Transfer of Multiple Drops (MTMD) Algorithm which was later refined to become another algorithm named the Mass Transfer Steady State (MTSS) Algorithm. …”
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17
Parameter estimation of multicomponent transient signals using deconvolution and ARMA modelling techniques
Published 2003“…Some computer simulation results are presented to justify the need for this modified method of analysis. …”
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Accurate numerical treatment on a stochastic SIR epidemic model with optimal control strategy
Published 2022“…The analytic-numeric New Iterative Method failed to deliver accurate solution for the large time domain. A new reliable algorithm based on NIM, the coupling of the Laplace transforms, and the New Iterative method is called Modified New Iterative Method (MNIM) which is presented to enhance the validity domain of NIM techniques. …”
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19
Parametric modelling of a TRMS using dynamic spread factor particle swarm optimisation
Published 2009“…The proposed method formulates a modified inertia weight algorithm by using a dynamic spread factor (SF). The inertia weight plays an important role in terms of balancing both the global and local search. …”
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Proceeding Paper -
20
A Subspace Approach for Extracting Signals Highly Corrupted by Colored Noise
Published 2010“…For validation purposes, the pre- and post-modified algorithms have been assessed in their abilities to extract visual evoked potentials (VEPs) that are corrupted by colored electroencephalogram (EEG) noise. …”
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