Search Results - (( parallel optimization methods algorithm ) OR ( based optimization model algorithm ))*
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Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures
Published 2020“…For these reasons, to improve the time and accuracy of the coverage in population-based meta-heuristics and their utilization in HPAs, this thesis presents a novel optimization algorithm called the Raccoon Optimization Algorithm (ROA). …”
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Voting algorithms for large scale fault-tolerant systems
Published 2011“…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
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OPTIMIZATION OF HYBRID-FUZZY CONTROLLER FOR SERVOMOTOR CONTROL USING A MODIFIED GENETIC ALGORITHM
Published 2011“…In this thesis, a new optimization GA-based algorithm that emanates from modification of conventional GA to reduce the iterations number and the duration time, namely, semi-parallel operation genetic algorithm (SPOGA) is proposed. …”
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Sequential and parallel multiple tabu search algorithm for multiobjective urban transit scheduling problems
Published 2018“…Additionally, the MTS algorithm is also implemented in parallel computing to produce parallel MTS for generating comparable solutions in shorter computational times. …”
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5
Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System
Published 2019“…In this paper, the particle swan optimization algorithm (PSO) was used to obtain an optimal set of initial parameters for Reduce Kernel FLN (RK-FLN), thus, creating an optimal RKFLN classifier named PSO-RKELM. …”
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Process Planning Optimization In Reconfigurable Manufacturing Systems
Published 2008“…Therefore, this study explores how to model reconfigurable manufacturing activities in an optimization perspective and how to develop and select appropriate non-conventional optimization techniques for reconfigurable process planning.In this study, a new approach to modeling Manufacturing Process Planning Optimization (MPPO) was developed by extending the concept of manufacturing optimization through a decoupled optimization method. …”
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A parallel ensemble learning model for fault detection and diagnosis of industrial machinery
Published 2023“…The base learners adopt a hybrid Back-Propagation (BP) and Particle Swarm Optimization (PSO) algorithms to exploit the corresponding local and global optimization capabilities for identifying optimal features and improving FDD performance. …”
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Minimizing machining airtime motion with an ant colony algorithm
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Design of low order quantitative feedback theory and H-infinity-based controllers using particle swarm optimisation for a pneumatic actuator system
Published 2010“…The PSO algorithm is used to optimize the loop-shaping step (subject to QFT constraints), which is performed manually in the standard QFT control design. …”
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Multi-objectives process optimization in end milling process of aluminium alloy 6061-T6 using genetic algorithm
Published 2024“…The optimum parameters were determined according to the design flow, constraints value and mathematical algorithm. Based on MOGA-II analysis, every workflow generated 1600 feasible solutions for optimization that meet the design space requirement. …”
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Restoration planning strategy of transmission system based on optimal energizing time of sectionalizing islands / Dian Najihah Abu Talib
Published 2019“…The initial solution is important to guide the optimization methods in finding the optimal solution. …”
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A Dual Recurrent Neural Network-based Hybrid Approach for Solving Convex Quadratic Bi-Level Programming Problem
Published 2020“…Apart from that, there are still a few utilizations of hybrid NN-based methods for solving BLPPs. Hence, we believe the proposed algorithm will contribute to solving quadratic-BLPPs involved in various engineering, management, and finance applications. …”
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Simulated kalman filter (SKF) based image template matching for distance measurement by using stereo vision system
Published 2018“…In this study, Simulated Kalman Filter (SKF) is applied to image template matching application as the optimization algorithm. SKF is compared with conventional algorithms for image template matching which are performance index value (PIM) and correlation by using DC components of image (TMC) and by using power of images (TMP) methods. …”
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14
Online system identification development based on recursive weighted least square neural networks of nonlinear hammerstein and wiener models.
Published 2022“…Best Hammerstein parallel NN polynomial based model and series-parallel NN polynomial model are 88.75% and 93.9% respectively, for best Hammerstein parallel NN sigmoid based model and series-parallel NN sigmoid based model 78.26% and 95.95% respectively, and for best Hammerstein parallel NN hyperbolic tangent based model and series-parallel NN hyperbolic tangent based model 70.7% and 96.4% respectively. …”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method
Published 2024thesis::doctoral thesis -
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Dual search maximum power point algorithm based on mathematical analysis under partially-shaded conditions
Published 2016“…In the first group, the conventional techniques are combined with other techniques and the second group is based on the optimization methods. One of the main challenges of MPPT techniques under PSCs is ability of the algorithms to find the GMPP faster with minimal oscillation in power. …”
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Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks
Published 2025thesis::doctoral thesis -
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Hybrid ANN and Artificial Cooperative Search Algorithm to Forecast Short-Term Electricity Price in De-Regulated Electricity Market
Published 2019“…Finally, the simulation results validated the premise of the proposed hybrid method through enhanced accuracy compared to the results acquired by implementing hybrid support vector machine (SVM) and hybrid ANN optimization methods. © 2013 IEEE.…”
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