Search Results - (( parameter implementation means algorithm ) OR ( parameter optimization based algorithm ))
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1
Enhanced gravitational search algorithm for nano-process parameter optimization problem / Norlina Mohd Sabri
Published 2020“…Based on the capabilities of the metaheuristic algorithms, this research is proposing the enhanced Gravitational Search Algorithm (eGSA) to solve the nano-process parameter optimization problem. …”
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2
Effectiveness of Nature-Inspired Algorithms using ANFIS for Blade Design Optimization and Wind Turbine Efficiency
Published 2019“…It was found that the optimized blade design parameters were obtained using an ABC algorithm with the maximum value power coefficient higher than ACO and PSO. …”
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3
Effectiveness of nature-inspired algorithms using ANFIS for blade design optimization and wind turbine efficiency
Published 2019“…It was found that the optimized blade design parameters were obtained using an ABC algorithm with the maximum value power coefficient higher than ACO and PSO. …”
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Perovskite lattice constant prediction framework using optimized artificial neural network and fuzzy logic models by metaheuristic algorithms
Published 2023“…The identification of optimized parameters for the ANN and fuzzy logic models is accomplished using innovative metaheuristic algorithms such as, Particle Swarm Optimization (PSO), Invasive Weed Optimization (IWO) and Imperialist Competitive Algorithm (ICA). …”
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5
Identification of continuous-time model of hammerstein system using modified multi-verse optimizer
Published 2021“…his thesis implements a novel nature-inspired metaheuristic optimization algorithm, namely the modified Multi-Verse Optimizer (mMVO) algorithm, to identify the continuous-time model of Hammerstein system. …”
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6
An efficient control implementation for inverter based harmony serach algorithm
Published 2017“…This research implements a PI controller based on harmony search (HS) optimization algorithm for voltage source inverter to improve the output performance under step load change conditions. …”
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7
An Efficient Control Implementation for Inverter Based Harmony Search Algorithm
Published 2017“…This research implements a PI controller based on harmony search (HS) optimization algorithm for voltage source inverter to improve the output performance under step load change conditions. …”
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8
A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…The research starts with developing the hybrid deep learning model consisting of DNN and a K-Means Clustering Algorithm. Then, the developed algorithm is implemented to estimate the parameters of the Lorenz system. …”
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9
Hybrid bat algorithm-artificial neural network for modeling operating photovoltaic module temperature: article / Noor Rasyidah Hussin
Published 2014“…In other words, the implemented bat algorithm in neural network structure is to get global optimization in order to minimize mean absolute percentage error, MAPE. …”
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Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar
Published 2019“…In addition, ANFIS approach is implemented to predict the �436�45D of wind turbine blades for investigation of algorithms performance based on Coefficient Determination (R2) and Root Mean Square Error (RMSE). …”
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11
Hybrid bat algorithm hybrid-artificial neural network for modeling operating photovoltaic module temperature / Noor Rasyidah Hussin
Published 2014“…In other words, the implemented bat algorithm in neural network structure is to get global optimization in order to minimize mean absolute percentage error, MAPE. …”
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12
Experimental implementation controlled SPWM inverter based harmony search algorithm
Published 2023Article -
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Improved flower pollination optimization algorithm based on swap operator and dynamic switch probability selection
Published 2023“…The proposed algorithm is ranked first among the stated algorithms with respect to its performance in getting the optimal solution…”
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14
An efficient control implementation for inverter based harmony search algorithm
Published 2023“…This research implements a PI controller based on harmony search (HS) optimization algorithm for voltage source inverter to improve the output performance under step load change conditions. …”
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15
Experimental implementation controlled SPWM inverter based harmony search algorithm
Published 2017“…The mean absolute error (MAE) formula is used as an objective function with the HS algorithm in finding the adaptive values of  and  parameters to minimize the error of the inverter output voltage. …”
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16
Agents for Fuzzy Indices of Reliability Power System with Uncertainty Using Monte Carlo Algorithm
Published 2014“…Two agents are developed based on fuzzy parameters of Monte Carlo i.e. current with its means and variances; the other agent is the probability of outage capacity for each state. …”
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17
Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems
Published 2019“…Hence, a memory-based optimization tool has good potential to retain the optimal design parameter during the PID tuning process. …”
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18
Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems
Published 2019“…Hence, a memory-based optimization tool has good potential to retain the optimal design parameter during the PID tuning process. …”
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19
The effect of job satisfaction on the relationship between organizational culture and organizational performance
Published 2023“…The proposed algorithm is ranked first among the stated algorithms with respect to its performance in getting the optimal solution…”
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20
Novel chewing cycle approach for peak detection algorithm of chew count estimation
Published 2025“…The chewing dataset comprises signals collected from 20 participants consuming eight different food types, with proximity sensors (PSs) detecting temporalis muscle activity. The peak detection algorithm identifies key signal features, while PSO optimizes the peak prominence and width parameters to minimize the mean absolute error (MAE) in chew count estimation. …”
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