Search Results - (( using set method algorithm ) OR ( parallel optimization based algorithm ))
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1
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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2
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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3
Investigation on the dynamic of computation of semi autonomous evolutionary computation for syntactic optimization of a set of programming codes
Published 2007“…They have to be optimized for parallel execution while some parts still do have sequential execution due to data dependencies, which makes the optimization problem two folds, parallel and serial. …”
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4
PID Parameters Improvement for AGC in Three Parallel-Connected Power Systems
Published 2016“…The optimal parameters of the PID scheme optimized by the proposed MS algorithm are compared with that one’s obtained by GA algorithm, and the proposed method has proven that its performance is more efficient and improved as well. …”
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5
Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems
Published 2022“…To achieve this goal, an improved Teaching Learning-Based Optimization (ITLBO) algorithm was proposed in dealing with subset feature selection. …”
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6
Distributed parallel deep learning with a hybrid backpropagation-particle swarm optimization for community detection in large complex networks
Published 2022“…Next, the method is integrated with two optimization algorithms: (1) backpropagation (BP), which optimizes deep learning locally within each local chunk of the CN; (2) particle swarm optimization (PSO), which is used to improve the BP optimization involving all CN chunks. …”
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Article -
7
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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8
Web based personalized university timetable for UiTM students using genetic algorithm / Mohd Radhi Fauzan Jamli and Ahmad Firdaus Ahmad Fadzil
Published 2024“…Future work entails enhancing system robustness through comprehensive contingency planning, real-time data integration, and algorithmic optimization, with a focus on refining the genetic algorithm and exploring parallel processing techniques to further enhance efficiency and scalability.…”
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Restoration planning strategy of transmission system based on optimal energizing time of sectionalizing islands / Dian Najihah Abu Talib
Published 2019“…Modification and simplification using parallel processing are done for both methods to grossly search the optimal solution and to minimize the program running time, respectively. …”
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10
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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11
Dynamic partitioning and data allocation method on heterogeneous architecture / Muhammad Helmi Rosli
Published 2015“…Each experiment highlight the advantages and disadvantages of the experimental architecture.The disadvantages from each experiment prompts the design of dynamic parallel partitioning and allocating framework. The case study use for this experiment is Sobel edge detection algorithm. …”
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12
Development of a multi-objective optimization model for transport and environment in a closed-loop automotive supply chain
Published 2014“…After that a Meta-heuristic method is used for finding the global optimum solution. …”
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13
Scheduling dynamic cellular manufacturing systems in the presence of cost uncertainty using heuristic method
Published 2016“…Then, design of experiments is used to examine the sensitivity of the parameters of each solving algorithm using Taguchi method. …”
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14
An Improved Fuzzy Parallel Distributed –Like Controller for Multi-Input Multi-Output Twin Rotor System
Published 2009“…Twin Rotor Multi Input Multi Output (MIMO) System (TRMS) is a laboratory set-up design for which it has been used for control experiments, control theories developments, and applications of the autonomous helicopter. …”
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15
Performance Comparison of Parallel Bees Algorithm on Rosenbrock Function
Published 2012“…This thesis presents the parallel Bees Algorithm as a new approach for optimizing the last results for the Bees Algorithm. …”
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16
Parallel distributed computational microcontroller system for adaptive antenna downlink transmitter power optimization
Published 2023Subjects:Article -
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Design and implemtation of a real-time adaptive learning algorithm controller for a 3-DOF parallel manipulator / Mustafa Jabbar Hayyawi
Published 2016“…Performance indices such as workspace, dexterity and stiffness, of the parallel manipulator are studied. The parallel manipulator is optimized based on the performance indices to obtain on the optimal design parameters for achieved maximum performance of the parallel manipulator. …”
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Student Project -
19
A review of genetic algorithms and parallel genetic algorithms on Graphics Processing Unit (GPU)
Published 2013“…Genetic Algorithms (GAs) is proven to be effective in solving many optimization tasks. …”
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20
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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