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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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Effects of control techniques and damper constraint on the performance of a semi-active magnetorheological damper
Published 2005“…In this study, a number of semi-active control algorithms namely modified skyhook, modified groundhook and modified hybrid skyhook-groundhook controllers are evaluated to be used with a magnetorheological damper. …”
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A New Technique To Design Coating Structure For Energy Saving Glass Using The Genetic Algorithm
Published 2017“…After modifying these shapes using the Genetic algorithm and Parallel Genetic algorithm, the outputs are simulated in the Computer Simulation Technology (CST) simulation software. …”
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Improved ADALINE Harmonics Extraction Algorithm for Boosting Performance of Photovoltaic Shunt Active Power Filter under Dynamic Operations
Published 2016“…It performs well in both steady state and dynamic operations as compared to the Modified W-H ADALINE algorithm.…”
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Improved ADALINE harmonics extraction algorithm for boosting performance of photovoltaic shunt active power filter under dynamic operations
Published 2016“…It performs well in both steady state and dynamic operations as compared to the Modified W-H ADALINE algorithm.…”
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A functional link neural network with modified cuckoo search for prediction tasks
Published 2017“…The impact of temperature, relative humidity and ozone changes bring a sharp warming climate. These changes can cause extreme consequences such as floods, hurricanes, heat waves and droughts. …”
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An improved particle swarm optimization (PSO) based MPPT for PV With reduced steady-state oscillation
Published 2012“…To evaluate the effectiveness of the proposed method, MATLAB simulations are carried out under very challenging conditions, namely step changes in irradiance, step changes in load, and partial shading of the PV array. …”
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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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Efficiency of 4253HT smoothers in extracting signal from noise and their applications in forecasting
Published 2019“…The performance of the modified compound smoothers was assessed via simulation. …”
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Dual search maximum power point algorithm based on mathematical analysis under partially-shaded conditions
Published 2016“…In this work, the perturb and observation (P&O) method based on duty cycle adjustment is introduced, which is modified to increase speed of the search and also to reduce the oscillation.The simulation and experimental works have been performed to investigate behavior and performance of the proposed algorithm. …”
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Modified least trimmed squares method for face recognition / Nur Azimah Abdul Rahim
Published 2018“…The genetic algorithm configuration for n (number of observations) and p (parameter) was changed to assess the performance of modified method. …”
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On The Switching Control Of The DC–DC Zeta Converter Operating In Continuous Conduction Mode
Published 2021“…By applying spatial regularization, a modified switching control algorithm reduces the switching frequency and keeps the state-trajectory around a neighbourhood of the operating point. …”
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Using adaptive safe experimentation dynamics algorithm for maximizing wind farm power
Published 2022“…This research presents a model-free strategy for increasing wind farm power generation based on the Adaptive Safe Experimentation Dynamics Algorithm (ASEDA). The ASEDA method is an improved version of the Safe Experimentation Dynamics (SED) algorithm that modifies the current tuning variable to respond to the changes in the objective function. …”
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A proposed framework for fish behaviors based on boid simulator
Published 2016“…This paper proposed a framework to simulate school of fishes of heterogeneous behaviours using the modified classical boid algorithm.The keystone of this paper is to allow flexible adaptations by two-level approaches where autonomous agent can instantly changes its micro- and macro behaviours through the parameter alteration.This study focuses on the genus Cyprinus (fish) that have distinguished varieties such as color, pattern and scale.This type of fish is well suited for computational simulation as individual fish can be easily tracked due to its discrete characters. …”
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Photovoltaic shunt active power filter based on indirect self-charging with step size error cancellation and simplified adaptive linear neuron
Published 2017“…From both simulation and experimental results, PV SAPF with both proposed algorithms show better performances as compared to the existing algorithms. …”
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Combination of perturb and observe with online sequential extreme learning machine for photovoltaic system maximum power point tracking
Published 2018“…From different MPPT techniques previously proposed, the online sequential extreme learning machine algorithm and conventional perturb and observe are combined together as a proposed MPPT algorithm. …”
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Using adaptive safe experimentation dynamics algorithm for maximizing wind farm power production
Published 2022“…This research presents a model-free strategy for increasing wind farm power generation based on the Adaptive Safe Experimentation Dynamics Algorithm (ASEDA). The ASEDA method is an improved version of the Safe Experimentation Dynamics (SED) algorithm that modifies the current tuning variable to respond to the changes in the objective function. …”
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The effect of adaptive parameters on the performance of back propagation
Published 2012“…Thus, this research proposed a new method known as Back Propagation Gradient Descent with Adaptive Gain, Adaptive Momentum and Adaptive Learning Rate (BPGD-AGAMAL) which modifies the existing Back Propagation Gradient Descent algorithm by adaptively changing the gain, momentum coefficient and learning rate. …”
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Use of AR Block Processing for Estimating the State Variables of Power System
Published 2008“…Samples of the local utility network for 103-bus parameter are collected and simulated using Burg and Modified Covariance algorithm to estimate the state variables. …”
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