Search Results - (( re evaluation method algorithm ) OR ( parameters variation _ algorithm ))
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A hybrid grey wolf assisted-sparrow search algorithm for frequency control of RE integrated system
Published 2023“…Moreover, the robustness of the proffered method is also evaluated under the random varying load, variation of HPS system parameter, and weather intermittency of RE resources in real-time conditions. …”
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Design of intelligent control system and its application on fabricated conveyor belt grain dryer
Published 2011“…These EAs overcome a common problem encountered in derivative-based learning methods, which is the necessity for the teaching signal when applying the ANIFIS as a controller.To demonstrate the effectiveness of the proposed controller, several non-linear plant models were used to evaluate its performance in terms of control accuracy, generalization ability, and robustness against external disturbances and parameter variations in the controlled system. …”
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Segmentation of MRI brain images using statistical approaches
Published 2011“…The non-Local means (NL-means) algorithm is a state-of-the art neighbourhood-based noisereduction method which is time-consuming and its accuracy can be improved. …”
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Design of low order quantitative feedback theory and H-infinity-based controllers using particle swarm optimisation for a pneumatic actuator system
Published 2010“…These algorithms are designed to achieve the robustness over a wide range of system parameters change and disturbances. …”
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Removal of heavy metals from water by functionalized carbon nanotubes with deep eutectic solvents: An artificial neural network approach / Seef Saadi Fiyadh
Published 2019“…The best result achieved for Pb2+ removal using ANFIS algorithm is with RE 7.078%. For As3+ removal using different adsorbents, two algorithms were applied for the modelling, the feed-forward back-propagation maximum RE achieved is 5.97% while, the NARX algorithm achieved better accuracy with maximum RE of 5.79%. …”
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Robustness Analysis Of An Optimized Controller Via Particle Swarm Algorithm
Published 2017“…The finding shows that the SMC that utilized the PSO algorithm parameters are capable to produce smaller robustness index values, which demonstrated better robustness characteristic in confront with the variation of the system parameter.…”
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Online auto-tuned proportional-integral controller using particle swarm optimization for dual active bridge DC-DC converter
Published 2021“…Ultimately, an online auto-tuned PI using PSO (OPSO-PI) was proposed to produce higher robustness than the APSO-PI. The OPSO-PI with re-tuning approach allows the update process of Kp and Ki parameters concerning the system change. …”
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Voltage Variation Analysis By Using Gabor Transform
Published 2019“…The parameters extracted can detect the voltage variation signals successfully. …”
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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“…This research suggests an evolutionary algorithm that incorporates the variational techniques mentioned above, which will be combined by a certain ratio, and the specific computational procedure. …”
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Performance of particle swarm optimization under different range of direct current motor's moment of inertia / Mohd Azri Abdul Aziz
Published 2018“…A prevalent application is a Direct Current (DC) motor control system with variations in parameters value have been used. Moment of inertia is one of the essential parameters of a DC motor which can affect the transient response including rise time, settling time, overshoot and steady state error. …”
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Decentralized Adaptive Pi With Adaptive Interaction Algorithm Of Wastewater Treatment Plant
Published 2014“…The Pi controller parameters are obtained by using simple updating algorithm developed based on adaptive interaction theory. …”
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Improved Differential Evolution-Based MPPT Algorithm Using SEPIC for PV Systems Under Partial Shading Conditions and Load Variation
Published 2018“…The main contribution of the proposed algorithm are the following: capability in tracking GMPP and faster respond against load variation; optimization algorithm can search for the GMPP within a larger operating region as it is implemented by using a single-ended primary-inductor converter; and easy tuning as less parameter has to be set in the algorithm. …”
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Hybrid Control of A Quadrotor System Carrying Suspended Payload With Parameter Variations
Published 2025thesis::master thesis -
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Performance of particle swarm optimization under different range of direct current motor's moment of inertia / Mohd Azri Abdul Aziz
Published 2018“…A prevalent application is a Direct Current (DC) motor control system with variations in parameters value have been used. Moment of inertia is one of the essential parameters of a DC motor which can affect the transient response including rise time, settling time, overshoot and steady state error. …”
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Hybrid metaheuristic method for clustering in wireless sensor networks / Bryan Raj Peter Jabaraj
Published 2023“…As such, this thesis proposes a hybrid metaheuristic method that consists of Sperm Swarm Optimization (SSO) algorithm and Genetic Algorithm (GA), which is termed HSSOGA. …”
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A review: Use of evolutionary algorithm for optimisation of machining parameters
Published 2021“…Lately, evolutionary algorithm, statistical approaches such as genetic algorithm (GA), particle swarm optimisation (PSO), and cuckoo search algorithm (CSA) have been utilised in simultaneous optimisation of the parameters of the desired outputs and its great potential in optimising machining processes is recognisable.…”
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Classification of Learner Retention using Machine Learning Approaches
Published 2021“…The performance of these algorithms was evaluated based on accuracy, precision, recall, and f-measure. …”
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An analysis of the parameter modifications in varieties of harmony search algorithm
Published 2014“…Based on the description of the fundamental concept of HS, recent variations of the extended HS were analyzed focusing on its algorithm’s theory as well as its fundamental and primary concepts. …”
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