Search Results - (( data extraction max algorithm ) OR ( parallel evaluation method algorithm ))
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Parallel Execution of Runge-Kutta Methods for Solving Ordinary Differential Equations
Published 2004“…The method used here is actually have been tailored made for the purpose of parallel machine where the subsequent functions evaluations do not depend on the previous function evaluations. …”
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Thesis -
2
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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3
Enhancing performance of XTS cryptography mode of operation using parallel design
Published 2009“…In addition, the parallel XTS mode was also simulated using Twofish and RC6 encryption algorithms. …”
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4
Parallel execution of diagonally implicit Runge-Kutta methods for solving IVPs.
Published 2009“…Diagonally Implicit Runge-Kutta (DIRK) methods are amongst the most useful and cost-effective methods for solving initial value problems but the dependency of the functions evaluations on the previous functions evaluations makes DIRK method not so favourable for parallel computers. …”
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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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Analysis of evolutionary computing performance via mapreduce parallel processing architecture / Ahmad Firdaus Ahmad Fadzil
Published 2014“…MR is an emerging parallel processing framework that hides the complex parallelization processes by employing the functional abstraction of "map and reduce" The Performance of the parallelized GA via MR and PSO via MR are evaluated using an analogous case study to find out the speedup and efficiency in order to measure the scalability of both proposed algorithms. …”
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8
Simulating Electrohydrodynamic Ion-Drag Pumping on Distributed Parallel Computing Systems
Published 2017“…For that reason, a Data Parallel Algorithm for EHD model (DPA-EHD) is designed. …”
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Data normalization techniques in swarm-based forecasting models for energy commodity spot price
Published 2014“…Data mining is a fundamental technique in identifying patterns from large data sets.The extracted facts and patterns contribute in various domains such as marketing, forecasting, and medical.Prior to that, data are consolidated so that the resulting mining process may be more efficient.This study investigates the effect of different data normalization techniques.which are Min-max, Z-score and decimal scaling, on Swarm-based forecasting models.Recent swarm intelligence algorithms employed includes the Grey Wolf Optimizer (GWO) and Artificial Bee Colony (ABC).Forecasting models are later developed to predict the daily spot price of crude oil and gasoline.Results showed that GWO works better with Z-score normalization technique while ABC produces better accuracy with the Min-Max.Nevertheless, the GWO is more superior than ABC as its model generates the highest accuracy for both crude oil and gasoline price.Such a result indicates that GWO is a promising competitor in the family of swarm intelligence algorithms.…”
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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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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 -
12
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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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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Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures
Published 2020“…The first step lies at the modelling of parallel applications running on heterogeneous parallel computers. …”
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Thesis -
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ANALYSIS OF BIOSENSOR PHYSIOLOGICAL SIGNALS FOR ASSESSMENT OF NEUROLOGICAL STATUS
Published 2018“…The extracted features are then fed into the Support Vector Machines (SVM) as well as the Ensemble Classifier which is a supervised learning model with associated learning algorithm that helps us to analyze the data for classification of neurological status of the subjects. …”
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Final Year Project -
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Solving ordinary differential equations using block multistep method
Published 2011“…The parallelism across the system is considered for the implementation of the parallel block methods. …”
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Efficient 3D temperature propagation for laser glass interaction
Published 2008“…The performance evaluations of the algorithm are increasing in terms of speed-up, efficiency and effectiveness.…”
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Malaysian license plate recognition system using Convolutional Neural Network (CNN) on web application / Nur Farahana Mahmud
Published 2022“…Training and validation data are split 80:20. The obtained sample image will first undergo pre-processing and character extraction. 3 layers of a Convolutional Neural Network (CNN) model that contain convolutional, max pooling, flatten and dense were created and further trained. …”
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Student Project -
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Parallel system for abnormal cell growth prediction based on fast numerical simulation
Published 2010“…The development of the prediction system is the combinations of the parallel algorithms, open source software on Linux environment and distributed multiprocessor system. …”
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