Search Results - parallel evaluation ((method algorithm) OR (((search algorithm) OR (based algorithm))))
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1
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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Thesis -
2
Dual search maximum power point algorithm based on mathematical analysis under partially-shaded conditions
Published 2016“…In evaluation part, the DSMPP algorithm has been compared with two other methods.According to both simulation and experimental results, by implementing the DSMPP technique, the GMPP can be obtained faster. …”
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Thesis -
3
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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4
Single and Multiple variables control using Tree Physiology Optimization
Published 2017“…The exploration is amplified from roots growth counterparts. In the proposed method, each shoot from each branch search for possible solution in parallel and the fitness is evaluated based on all best values found by branch search. …”
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An Experimental Study on Relationship between Performance and Energy Consumption of Serial and Parallel Text Searching Algorithm.
Published 2013“…How to reduce execution time in searching large amount of data? In this paper, text searching algorithm is using to study the relationship between performance of computer and amount of energy produced in serial and parallel text searching algorithm. …”
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Final Year Project -
6
Improved criteria determination of an automated negative lightning return strokes characterisation using Brute-Force search algorithm
Published 2021“…The criteria for each of the negative lightning return strokes parameters were established and defined based on specific mathematical equations. Accordingly, the proposed Brute-Force search algorithm characterised the negative lightning return strokes parameters based on the seven parameters. …”
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7
Process Planning Optimization In Reconfigurable Manufacturing Systems
Published 2008“…The five (5) AADTs include; a variant of the simulated annealing algorithm that implements heuristic knowledge at critical decision points, two (2) cooperative search schemes based on a “loose hybridization” of the Boltzmann Machine algorithm with (i) simulated annealing, and (ii) genetic algorithm search techniques, and two (2) modified genetic algorithms. …”
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8
Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems
Published 2022“…Meanwhile, an improved parallel Jaya (IPJAYA) algorithm was proposed for searching the best parameters (C, Gama) values of SVM. …”
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9
Hybrid ANN and Artificial Cooperative Search Algorithm to Forecast Short-Term Electricity Price in De-Regulated Electricity Market
Published 2019“…Therefore, this research proposes a hybrid method for electricity price forecasting via artificial neural network (ANN) and artificial cooperative search algorithm (ACS). …”
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PMT : opposition based learning technique for enhancing metaheuristic algorithms performance
Published 2020“…To evaluate the PMT’s performance and adaptability, the PMT was applied to four contemporary metaheuristic algorithms, Differential Evolution, Particle Swarm Optimization, Simulated Annealing, and Whale Optimization Algorithm, to solve 15 well-known benchmark functions as well as 2 real world problems based on the welded beam design and pressure vessel design. …”
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Thesis -
11
Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems
Published 2014“…To implement the parallel algorithms a distributed parallel computing laboratory using easily available low cost computers is setup. …”
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12
PMT: opposition-based learning technique for enhancing meta-heuristic performance
Published 2019“…The experimentally, the PMT shows promising results by accelerating the convergence rate against the original algorithms with the same number of fitness evaluations.…”
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13
Communication and computational cost on parallel algorithm of PDE elliptic type
Published 2009“…Due to this needs, this paper presents the parallel performance evaluations of algorithms that will be discussed in term of communication and computational cost.…”
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Book Section -
14
Authenticating sensitive diacritical texts using residual, data representation and pattern matching methods / Saqib Iqbal Hakak
Published 2018“…The searching of halves is achieved through two different algorithms based on the split approach and the parallel approach respectively. …”
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15
Parallel execution of diagonally implicit Runge-Kutta methods for solving IVPs.
Published 2009“…Numerical results based on the sequential and parallel modes are tabulated and compared, which shows the advantage of the algorithms based on the parallel mode.…”
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A spark-based parallel fuzzy C median algorithm for web log big data
Published 2022“…Based on the Rand Index and SSE (sum of squared error), the parallel Fuzzy C median algorithm's performance is evaluated in the PySpark platform. …”
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Improving parallel self-organizing map using heterogeneous uniform memory access / Muhammad Firdaus Mustapha
Published 2018“…Finally, this research designs and implements an enhanced parallel SOM architecture through combining two parallel methods which are network and data partitioning. …”
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Thesis -
18
Hybrid harmony search-artificial intelligence models in credit scoring
Published 2019“…Genetic Algorithm (GA) has been the dominant method and other MA being attempted recently has shown the potential of MA to perform hyperparameters tuning. …”
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Thesis -
19
The Parallel Fuzzy C-Median Clustering Algorithm Using Spark for the Big Data
Published 2024“…Therefore, we develop a Parallel Fuzzy C-Median Clustering Algorithm Using Spark for Big Data that can handle large datasets while maintaining high accuracy and scalability. …”
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