Search Results - (( based classification method algorithm ) OR ( parallel evaluation method algorithm ))*
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An Improve k-NN Classifier using Similarity Distance Plot-Data Reduction and Dask for Big Datasets
Published 2025“…The k-Nearest Neighbour (k-NN) algorithm is one of the most widely used Instance-Based Learning methods due to its simplicity and ease of implementation. …”
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Hybrid harmony search-artificial intelligence models in credit scoring
Published 2019“…Instead of the conventional Grid Search (GS) and manual tuning (MT) approaches, automated tuning with metaheuristics approach (MA) have also shown to be effective in this task. 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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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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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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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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Case Slicing Technique for Feature Selection
Published 2004“…CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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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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Knowledge base processing method based on text classification algorithm
Published 2023“…The text classification algorithm's knowledge base processing method utilizes existing data from the knowledge base to guide the construction and training of the classification model. …”
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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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Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach
Published 2009“…The method was developed based on the grid structure, whereby it was done to create a successful method of improving performance in classification. …”
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11
Grid base classifier in comparison to nonparametric methods in multiclass classification
Published 2010“…The method was developed based on the grid structure which was done to create a powerful method for classification. …”
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Aco-based feature selection algorithm for classification
Published 2022“…The modified graph clustering ant colony optimisation (MGCACO) algorithm is an effective FS method that was developed based on grouping the highly correlated features. …”
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An efficient and effective case classification method based on slicing
Published 2006“…This paper introduces a new classification method based on slicing techniques that was proposed for procedural programming languages. …”
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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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Real-time Traffic Classification Algorithm Based on Hybrid of Signature Statistical and Port to Identify Internet Applications
Published 2014“…The three common classification methods i.e. port, payload and statistics based have some limitations. …”
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Overview of metaheuristic: classification of population and trajectory
Published 2010“…An algorithm that applies a metaheuristic method is used when there are no specific methods to find a solution. …”
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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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A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network
Published 2014“…Among numerous artificial intelligence approaches, k-Nearest Neighbor algorithms, genetic algorithms, and artificial neural networks are considered as the most common and effective methods in classification problems in numerous studies. …”
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