Search Results - (( simulation optimization window algorithm ) OR ( simulation optimization means algorithm ))
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An optimized aggregate marker algorithm for bandwidth fairness improvement in classifying traffic networks
Published 2016“…This article analyses and evaluates a new time sliding window traffic marker algorithm called the Optimized time sliding window Three Colour Marker (OtswTCM). …”
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Simulation for dynamic patients scheduling based on many objective optimization and coordinator
Published 2024“…Taking both aspects, optimization and dynamic utilization, we propose a simulation for dynamic patient scheduling based on multi-objective optimization, window, and coordinator. …”
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Optimized clustering with modified K-means algorithm
Published 2021“…Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
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Simulation and Visualization of TSP Using Ant Colony Optimization
Published 2023“…The Travelling Salesman Problem (TSP) is a well-known algorithmic problem its main objective is optimization. …”
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Development of an education simulator for particle swarm optimization in solving economic dispatch problems: article / Mohd Hafiz Mat Hussain
Published 2009“…The developed simulator incorporated particle swarm optimizations (PSO) to solve the ED problems. …”
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Development of an education simulator for particle swarm optimization in solving economic dispatch problems / Mohd Hafiz Mat Hussain
Published 2009“…The developed simulator incorporated particle swarm optimizations (PSO) to solve the ED problems. …”
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Simulation of identifying shortest path walkway in library by using ant colony optimization
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Fair bandwidth distribution marking and scheduling algorithm in network traffic classification
Published 2019“…Second, an Optimized time sliding window packet marker (OTSWTCM) algorithm. …”
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Impact of evolutionary algorithm on optimization of nonconventional machining process parameters
Published 2025“…Using a Python environment, three evolutionary algorithms such as, Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Firefly Algorithm (FA), were simulated to evaluate their effectiveness in minimizing surface roughness (Ra). …”
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Determining optimal location of static VAR compensator by means of genetic algorithm
Published 2011“…This method is employed to optimize the stability of power system by means of maximizing distance to collapse point. …”
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Studying the Effect of Training Levenberg Marquardt Neural Network by Using Hybrid Meta-Heuristic Algorithms
Published 2016“…The simulation results show that the APSO-LM algorithm shows better performance than baseline algorithms in terms of convergence speed and Mean Squared Error (MSE).…”
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QTCP: an optimized and improved congestion control algorithm of high-speed TCP networks
Published 2011“…To overcome these problems Quick Transport Control Protocol (QTCP) algorithm based on optimizations of HS-TCP slow start algorithm and Additive Increase and Multiplicative Decrease (AIMD) algorithm have been proposed. …”
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Efficient Time-Varying q-Parameter Design for q-Incremental Least Mean Square Algorithm with Noisy Links
Published 2022“…The analytical results are validated through simulation. Finally, extensive simulations have been done to evaluate the performance of the proposed algorithm for various choices of optimal q-values. …”
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Optimalisation of a job scheduler in the grid environment by using fuzzy C-mean
Published 2007“…Simulation runs demonstrate that our algorithm leads to better results than the traditional algorithms for scheduling policies used in Grid environment.…”
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Modified K-Nearest Neighborhood Algorithm For Optimal Selection Of Distribution Centre In The Disaster Relief Operation
Published 2024thesis::master thesis -
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Studying the effect of training Levenberg Marquardt neural network by using hybrid meta-heuristic algorithms
Published 2016“…The simulation results show that the APSO-LM algorithm shows better performance than baseline algorithms in terms of convergence speed and Mean Squared Error (MSE).…”
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A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models
Published 2017“…These models are developed by integrating multilayer perceptron neural network and evolutionary optimization techniques. Genetic algorithm and simulated annealing techniques are used to optimize the control parameters of the neural network. …”
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Cluster optimization in VANET using MFO algorithm and K-Means clustering
Published 2023“…Proven to be an effective and efficient method for solving optimization problem. To design K-Means algorithm that portion nodes based on their proximities by optimize the distance between nodes within same cluster by assigning them to the closet cluster center. …”
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Optimized speed controller for induction motor drive using quantum lightning search algorithm
Published 2023Conference Paper
