Search Results - (( parameter optimization max algorithm ) OR ( based simulation based algorithm ))
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1
Prediction and multi-criteria-based schemes for seamless handover mechanism in mobile WiMAX networks
Published 2013“…It reduces the number of handovers by 29.7% and 26.9%, respectively, compared to the conventional RSSI based handover algorithm and the previous worked, mobility improved handover (MIHO) algorithm. …”
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2
Optimized scheme for efficient and scalable key management in IEEE 802.16e-based networks
Published 2015“…IEEE 802.16e uses multicast and broadcast service (MBS) as an efficient mechanism to distribute the same data concurrently to multiple mobile stations (MSs) through one Base Station. To generate, update and distribute the keys for secure communication over IEEE 802.16e, the MBS applies Multicast and Broadcast Rekeying Algorithm (MBRA) as a basic key management algorithm. …”
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3
The effect of pre-processing techniques and optimal parameters on BPNN for data classification
Published 2015“…In this research, a performance analysis based on different activation functions; gradient descent and gradient descent with momentum, for training the BP algorithm with pre-processing techniques was executed. …”
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4
Optimization of hydropower reservoir system using genetic algorithm for various climatic scenarios
Published 2015“…In order to increase the system efficiency and maximize the power generation, constructed operation models were optimized. To determine the optimum solution in each policy, real coded genetic algorithm is used as an optimization technique. …”
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5
Reactive approach for automating exploration and exploitation in ant colony optimization
Published 2016“…Ant colony optimization (ACO) algorithms can be used to solve nondeterministic polynomial hard problems. …”
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6
Ant colony optimization in dynamic environments
Published 2010“…The last objective of this thesis is to optimize the parameter settings of the best performing ant algorithm with local search. …”
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7
Improvement of Centralized Routing and Scheduling Using Cross-Layer Design and Multi-Slot Assignment in Wimax Mesh Networks
Published 2009“…This thesis proposes an optimized strategy namely cross-layer design in routing algorithms used find the best route for all SSs and scheduling algorithms, used to assign a time slot for each possible node transmission. …”
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8
Electric vehicle battery state of charge estimation using metaheuristic-optimized CatBoost algorithms
Published 2025“…A comprehensive data preprocessing pipeline was implemented, including missing value treatment, outlier removal, and feature normalization using Min-Max scaling. Three distinct metaheuristic algorithms were investigated: Barnacles Mating Optimizer (BMO), Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Whale Optimization Algorithm (WOA), each integrated with CatBoost to optimize critical parameters including learning rate, tree depth, regularization, and bagging temperature. …”
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9
Single Fitness Function to Optimize Energy using Genetic Algorithms for Wireless Sensor Network
Published 2024journal::journal article -
10
Design Optimization of a Gas Turbine Engine for Marine Applications: Off-Design Performance and Control System Considerations
Published 2022“…Meta-heuristic optimizations, namely a genetic algorithm (GA) and a whale optimization algorithm (WOA), are applied to optimize the designed control system. …”
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11
Optimization-based simulation algorithm for predictive-reactive job-shop scheduling of reconfigurable manufacturing systems
Published 2022“…This study is aimed to formulate an optimization-based algorithm with simulation tool to reduce the throughput time of complex RMS, which can comply with complex product allocations and flexible routings of the system. …”
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12
A simulation based fly optimisation algorithm for swarms of mini autonomous surface vehicles application
Published 2011“…Present paper intends to provide a detailed description of a new bio-inspired Metaheuristic Algorithm. Based on the detailed study of the Drosophila, the flowchart behaviour for the algorithm, code implementation, methodologies and simulation analysis, a novel Fly Optimization Algorithm (FOA) approach is presented. …”
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13
Simulated Kalman Filter: A Novel Estimation-based Metaheuristic Optimization Algorithm
Published 2016“…In this paper, a new population-based metaheuristic optimization algorithm, named Simulated Kalman Filter (SKF) is introduced. …”
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14
Incorporating the range-based method into GridSim for modeling task and resource heterogeneity
Published 2017“…However, most simulation studies that based on GridSim have not considered the nature of heterogeneity. …”
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15
Performance of Ad-Hoc on-Demand Distance Vector Discovery Algorithms Based On Packet Lifetime
Published 2008“…From the extensive simulations based on the performance metrics, the two proposed algorithms have shown distinct improvement and subsequently enhancing the performance of AODV.…”
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16
Adaptive Beamforming Algorithm based on Generalized Opposition-based Simulated Kalman Filter
Published 2016“…In this paper, a new population-based metaheuristic optimization algorithm named Generalized Opposition-based Simulated Kalman Filter (GOBSKF) is proposed as adaptive beamforming algorithm. …”
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17
Adaptive beamforming algorithm based on Simulated Kalman Filter
Published 2017“…A modified version of the SKF algorithm, named Opposition-Based SKF (OBSKF), introduced by K. …”
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18
Development of Simulated Annealing Based Scheduling Algorithm for Two Machines Flow Shop Problem
Published 2015“…Viewing as optimization problem and focusing on two machines, this research aims to develop a new Simulated Annealing based scheduling algorithm, called SA2M, for flow shop problem. …”
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19
Image Template Matching Based on Simulated Kalman Filter (SKF) Algorithm
Published 2018“…A novel approach to the image matching based on Simulated Kalman Filter (SKF) algorithm has been proposed in this paper. …”
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20
Opposition-based learning simulated kalman filter for Numerical optimization problems
Published 2016“…Simulated Kalman Filter (SKF) optimization algorithm is a population-based optimizer operated mainly based on Kalman filtering. …”
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