Search Results - (( simulation optimization using algorithm ) OR ( using active based algorithm ))
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1
Active power optimization based on non adaptive immune algorithm: article
Published 2010“…This paper presents a study of active power optimization based on non adaptive immune algorithm (NAIA) in power systems. …”
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2
Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation
Published 2022“…The proposed algorithm is simulated for simultaneous OPF-based conflicting objectives, respectively. …”
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Thesis -
3
Online DE optimization for Fuzzy-PID controller of semi-active suspension system featuring MR damper
Published 2022“…In this paper, MR fluid damper with Fuzzy-PID controller is examined to be optimized using a modified DE algorithm. However, in the Fuzzy-PID controller, the fuzzy logic algorithm is used to auto-tune the PID controller, but it cannot be considered as a fully real-time controller since the fuzzy algorithm uses a previous knowledge base built offline. …”
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4
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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Workflow optimization in distributed computing environment for stream-based data processing model / Saima Gulzar Ahmad
Published 2017“…This thesis proposes data-intensive workflow optimization algorithms. The first algorithm architecture consists of two phases a) workflow partitioning, and b) partitions mapping. …”
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6
Genetic algorithm based mass distribution optimization of quadruped leg robot for walking performance enhancement
Published 2013“…In this experiment, quadruped is used to perform repetition tests in simulated environment. …”
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7
Simulation for dynamic patients scheduling based on many objective optimization and coordinator
Published 2024“…Therefore, it treats PASP as a multi-objective dynamic optimization of a useful solution. NSGA-II is guaranteed 0.96 percent dominance over NSGA-II and 100 percent dominance of all other algorithms.…”
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Optimal power flow using hybrid firefly and particle swarm optimization algorithm
Published 2020“…In this paper, a novel, effective meta-heuristic, population-based Hybrid Firefly Particle Swarm Optimization (HFPSO) algorithm is applied to solve different non-linear and convex optimal power flow (OPF) problems. …”
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Optimization in active vibration control: virtual experimentation using COMSOL multiphysics - MATLAB integration
Published 2014“…Instead of using equation-based modeling for the system, the plant is a finite element model developed in COMSOL Multiphysics software, which later interfaced with the MATLAB-coded optimization algorithm using the Livelink for MATLAB feature. …”
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Proceeding Paper -
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Forecasting hydrological parameters for reservoir system utilizing artificial intelligent models and exploring their influence on operation performance
Published 2019“…The three different optimization algorithms used in this study are the genetic algorithm (GA), particle swarm optimization (PSO) algorithm and shark machine learning algorithm (SMLA). …”
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Optimization of supply chain management by simulation based RFID with XBEE Network
Published 2015“…In order to solve this problem, a simulation based “Multi-Colony Global Particle Swarm Optimization (MC-GPSO)” algorithm was developed. …”
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Cluster optimization in VANET using MFO algorithm and K-Means clustering
Published 2023“…Introduce MFO algorithm for simulate the movement behavior of moths and update the position based upon movements. …”
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Conference or Workshop Item -
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Voltage constrained optimal power flow based using genetic algorithm
Published 2015“…Simulation results of the three-phase voltage profi le along the tested feeder using the proposed method provide better results than other mentioned methods. …”
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14
A Single Objective Flower Pollination Algorithm for Modeling the Horizontal Flexible Plate System
Published 2020“…The performance of the developed model was then compared with the conventional algorithm known as recursive least square (RLS). The best model achieved in this study will be used as a platform of controller development using active vibration control technique.…”
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Proceeding -
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An intelligent framework for modelling and active vibration control of flexible structures
Published 2004“…The second controller design strategy is based on a cost function optimization using GAS. …”
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Active vibration control of a flexible beam structure using chaotic fractal search algorithm
Published 2017“…The accuracy of generated flexible beam model was validated using correlation and system stability tests. A PID controller incorporated with CFS optimization algorithm was employed to attenuate the unwanted vibration from the flexible beam system. …”
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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 this study, the performance of these three algorithms in obtaining the optimal blade design based on the �436�45D are investigated and compared. …”
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18
Optimal distributed generation and load shedding scheme using artificial bee colony- hill climbing algorithm considering voltage stability and losses indices
Published 2021“…To solve this problem, an optimal load shedding approach, integrated with optimal DG sizing is proposed using the ABC-HC algorithm. …”
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19
Cyber Terrorist Detection by using Integration of Krill Herd and Simulated Annealing Algorithms
Published 2024“…This paper presents a technique to detect cyber terrorists suspected activities over the net by integrating the Krill Herd and Simulated Annealing algorithms. …”
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A new ant based rule extraction algorithm for web classification
Published 2011“…Using Classifier-based attribute subset selection will reduce more attributes, but sacrifice the performance of the classifier.A hybrid ant colony optimization with simulated annealing algorithm to discover rules from data is proposed.The simulated annealing technique will minimize the problem of low quality discovered rule by an ant in a colony.The best rule for a colony will then be chosen and later the best rule among the colonies will be included in the rule set.The best rule for a colony will then be chosen and later the best rule among the colonies will be included in the rule set.The rule set is arranged in decreasing order of generation.Thirteen data sets which consist of discrete and continuous data were used to evaluate the performance of the proposed algorithm in terms of accuracy, number of rules and number of terms in the rules.Experimental results obtained from the proposed algorithm are comparable to the results of the Ant-Miner algorithm in terms of rule accuracy but are better in terms of rule simplicity.…”
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