Search Results - (( parameter simulation modified algorithm ) OR ( using simulation learning algorithm ))
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A harmony search-based learning algorithm for epileptic seizure prediction
Published 2016“…The proposed harmony search-based learning algorithm is used in the task of epileptic seizure prediction. …”
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The effect of adaptive parameters on the performance of back propagation
Published 2012“…The results show that the proposed algorithm extensively improves the learning process of conventional Back Propagation algorithm.…”
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Thesis -
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Effect of chaos noise on the learning ability of back propagation algorithm in feed forward neural network
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Working Paper -
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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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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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A modified weight optimisation for higher-order neural network in time series prediction
Published 2020“…The performance of MCS-MCMC learning algorithm was validated with several test functions and compared with those of MCS learning algorithm. …”
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Thesis -
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A Novel Hybrid Deep Learning Model Based on Simulated Annealing and Cuckoo Search Algorithms for Automatic Radiomics-Based COVID-19 Diagnosis
Published 2025“…To further enhance COVID-19 lesion estimation, novel optimization strategies, including a hybrid simulated annealing-cuckoo search (SA-CS) algorithm, are introduced alongside the original SA method. …”
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A novel islanding detection technique using modified Slantlet transform in multi-distributed generation
Published 2019“…A Harmony Search Algorithm (HSA) is used to optimally specify suitable scales of Slantlet transform and Slantlet decomposition levels for accurate islanding classification. …”
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The effect of pre-processing techniques and optimal parameters on BPNN for data classification
Published 2015“…It’s data-driven, self-adaptive, and non-linear capabilities channel it for use in processing at high speed and ability to learn the solution to a problem from a set of examples. …”
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Thesis -
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Information Theoretic-based Feature Selection for Machine Learning
Published 2018“…The second test evaluates IFS in a controlled study using simulated datasets. Moreover, the third test used ten natural domain datasets obtained from UCI Repository, in about fifteen different experiments, using three to four different Machine Learning Algorithms for performance evaluation. …”
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Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation
Published 2019“…Furthermore, to evaluate the efficiency of the proposed modified differential evolution for the training of ridgelet probabilistic neural network, four statistical search techniques, namely, particle swarm optimization, genetic algorithm, simulated angling, and classical differential evolution are used and their results are compared. …”
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Modelling of optimized hybrid debris flow using airborne laser scanning data in Malaysia
Published 2019“…The general objective of the study was the development of optimized hybrid debris flow models using airborne laser scanning data and Machine learning algorithms in Malaysia. …”
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Sensorless induction motor speed control for electric vehicles using enhanced hybrid flux estimator with ann-ifoc controller
Published 2022“…Artificial neural network (ANN)-field-oriented control (FOC) was used in the hybrid flux system. The function of the ANN was to improve speed-tracking performance, and the learning rate of the ANN inside the indirect FOC’s structure trained using the Levenberg-Marquardt (LM) algorithm was varied in order to increase speed-tracking accuracy when combined with the improved ANN speed controller. …”
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Thesis -
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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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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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Final Year Project / Dissertation / Thesis -
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Numerical simulations of agent navigation via half-sweep modified two-parameter over-relaxation (HSMTOR)
Published 2021“…A new method called Half-Sweep Modified Two-Parameter Over-Relaxation (HSMTOR) is used to solve the navigational problems. …”
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Proceedings -
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The PID controller parameter tuning based on a modified differential evolutionary optimization algorithm for the intelligent active vibration control of a combined single link robo...
Published 2025“…Here, in this research by comprising three of the most effective variational techniques now, a Modified Differential Evolutionary Optimization Algorithm (MDEOA) method is suggested to handle the challenge of adjusting the PID controller parameters for the Intelligent Active Vibration Control (IAVC) of a Combined Single Link Robotics Flexible Manipulator (CSLRFM) in order to reduce the undesired effects of vibration. …”
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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 -
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