Search Results - parallel selection ((((method algorithm) OR (sensor algorithm))) OR (means algorithm))
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1
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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2
Automated plant recognition system based on multi-objective parallel genetic algorithm and neural network
Published 2014“…To conclude, multi objective parallel genetic algorithm can automatically tune feed forward neural network to classify the dataset with a good classification rate.…”
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3
Recognizing complex human activities using hybrid feature selections based on an accelerometer sensor
Published 2017“…The performance of our work also been compared with several state-of-the-art of features for selection algorithms.…”
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4
Extreme air pollutant data analysis using classical and Bayesian approaches
Published 2015“…MTM algorithm is an extension of MH algorithm, designed to improve the convergence of MH algorithm by performing parallel computation. …”
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5
Parallel algorithms on some numerical techniques using PVM platform on a cluster of workstations
Published 2002“…In this paper, a few parallel algorithms are explained in solving one dimensional heat model problem using Parallel Virtual Machine (PVM). …”
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6
New CFAR algorithm and circuit development for radar receiver
Published 2020“…Therefore, the MSS-CA-CFAR is chosen to implement by practical digital circuit and there is another important feature in the MSS-CFAR algorithm that is parallel processing since the spike selection process is done at the same time with summing of samples process that makes this algorithm much less in processing time from any other algorithm using the same environment. …”
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7
Image classification using two dimensional wavelet coefficients with parallel computing
Published 2020“…This research algorithm demonstrated a very promising result with Support Vector Machines, this algorithm produces a 90% of accuracies whereas the decision tree algorithm gets 100% accuracies. …”
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Online simulation to monitor multiphase flow using laser source as transmitter
Published 2021“…In order to visualise the material inside the pipeline, parallel beam projection had been selected. However, while producing the image, some constraints such as diffraction and reflection in liquid medium will happen, where it will affect the flow accuracy of the result. …”
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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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Guided genetic algorithm for solving unrelated parallel machine scheduling problem with additional resources
Published 2022“…Additionally, an appropriate selection of GA operators was also experimented. The guide genetic algorithm (GGA) is not used to solve the unspecified dynamic UPMR. …”
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ROA-CONS: raccoon optimization job scheduling
Published 2021“…In comparison with other well-known job scheduling algorithms, the simulation assesses the effectiveness of the proposed method. …”
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Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System
Published 2020“…The proposed method combined the improved teaching-learning-based optimisation (ITLBO) algorithm, improved parallel JAYA (IPJAYA) algorithm, and support vector machine. …”
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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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14
Application Of Genetic Algorithms For Robust Parameter Optimization
Published 2010“…Genetic algorithms (GA) are fairly recent in this respect but afford a novel method of parameter optimization. …”
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Diverse cell interaction in dynamic cell sizing and VC-PGA cell priority selection method
Published 2002“…In this paper, the diverse interaction among cells is discussed.The preliminary description of forward link capacity gain on a single cell serves as groundwork for discussions on bi-directional impact of cell-pairs and the multifarious interactions of cells in a CDMA network.The diverse interaction of cells is then made analogous to that of community members in a virtual community in a genetic algorithm.The cell to be given highest priority cell over shrinking in the virtual community is selected by the virtual community parallel genetic algorithm (VC-PGA).By this method, the number of cell attenuations may be controlled, the emergence of coverage holes reduced and thus, the quality of service increased.…”
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16
The development of semantic meta-database: an ontology based semantic integration of biological databases
Published 2007“…The tool comprises two intelligent algorithms. The first algorithm combines parallel genetic algorithm with the split-and-merge algorithm. …”
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Intelligent classification algorithms in enhancing the performance of support vector machine
Published 2019“…This paper presents two intelligent algorithms that hybridized between ant colony optimization (ACO) and SVM for tuning SVM parameters and selecting feature subset without having to discretize the continuous values. …”
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Online Simulation To Monitor Multiphase Flow Using Laser Source As Transmitter
Published 2024journal::journal article -
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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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20
Effective software fault localization based on complex network theory / Abubakar Zakari
Published 2019“…This has led researchers to adopt approaches such as one bug-at-a-time debugging approach (OBA) and parallel debugging approach. However, using OBA debugging approach increases software time-to-delivery and potentially leads to more faults during regression testing, while utilizing k-mean clustering algorithm with Euclidean distance metric to group failed tests based on their execution profile similarity in parallel debugging approach is claimed to be problematic and inappropriate. …”
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