Search Results - parallel using ((((mining algorithm) OR (matching algorithm))) OR (learning algorithm))*
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Efficient Malware Detection And Response Model Using Enhanced Parallel Deep Learning (EPDL-MDR)
Published 2026“…Upon converting PE files to images, the deep learning pixel-matching algorithm identifies obscured malware features. …”
thesis::doctoral thesis -
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Measuring GPU-accelerated parallel SVM performance using large datasets for multi-class machine learning problem
Published 2023Conference Paper -
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Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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4
GPU-based odd and even hybrid string matching algorithm
Published 2016“…String matching is considered as one of the fundamental problems in computer science.Many computer applications provide the string matching utility for their users, and how fast one or more occurrences of a given pattern can be found in a text plays a prominent role in their user satisfaction.Although numerous algorithms and methods are available to solve the string matching problem, the remarkable increase in the amount of data which is produced and stored by modern computational devices demands researchers to find much more efficient ways for dealing with this issue.In this research, the Odd and Even (OE) hybrid string matching algorithm is redesigned to be executed on the Graphics Processing Unit (GPU), which can be utilized to reduce the burden of compute-intensive operations from the Central Processing Unit (CPU).In fact, capabilities of the GPU as a massively parallel processor are employed to enhance the performance of the existing hybrid string matching algorithms.Different types of data are used to evaluate the impact of parallelization and implementation of both algorithms on the GPU. …”
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Speeding up index construction with GPU for DNA data sequences
Published 2011“…Graphic processor unit (GPU) is used to parallelize a segment of an indexing algorithm. …”
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Conference or Workshop Item -
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Multithreaded Scalable Matching Algorithm For Intrusion Detection Systems
Published 2010“…Therefore, the performance of the existing algorithms needs to be improved both in sequential and parallel to enhance the speed of the detection engine used in SNORT-NIDS. …”
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7
Prognosis of early cervical carcinoma using gene expression profiling
Published 2015“…Data mining and machine learning have found considerable application thru the use of microarray expression profiling inspection. …”
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Proceeding Paper -
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Parallel execution of distributed SVM using MPI (CoDLib)
Published 2023“…Instead of using a single machine for parallel computing, multiple machines in a cluster are used. …”
Conference paper -
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Simulated kalman filter (SKF) based image template matching for distance measurement by using stereo vision system
Published 2018“…SKF is compared with conventional algorithms for image template matching which are performance index value (PIM) and correlation by using DC components of image (TMC) and by using power of images (TMP) methods. …”
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Design and implementation of a real-time adaptive learning algorithm controller for a 3-DOF parallel manipulator / Mustafa Jabbar Hayawi
Published 2015“…An electronic board, transistor relay driver circuit, is designed for the purpose of establishing communication interface between the computer, adaptive learning algorithm and the actuator mechanism. Design and development an adaptive learning algorithm controller ALAC of position the actuators is presented in real time parallel manipulator based on artificial neural network ANN. …”
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12
Fast and efficient sequential learning algorithms using direct-link RBF networks
Published 2003“…The dynamic DRBF network is trained using the recently proposed decomposed/parallel recursive Levenberg Marquardt (PRLM) algorithm by neglecting the interneuron weight interactions. …”
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Book Section -
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Effect Of The Addition Of Wastepaper To Concrete Mix
Published 2009“…Therefore, the performance of the existing algorithms needs to be improved both in sequential and parallel to enhance the speed of the detection engine used in SNORT-NIDS. …”
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Parallel batch self-organizing map on graphics processing unit using CUDA
Published 2018“…The most computationally expensive parts of its training algorithm (such as steps to compute distance between each data vector and neuron, and determining the Best Matching Unit based on minimum distance) are identified and mapped on GPU to be processed in parallel. …”
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Parallel batch self-organizing map on graphics processing unit using CUDA
Published 2018“…The most computationally expensive parts of its training algorithm (such as steps to compute distance between each data vector and neuron, and determining the Best Matching Unit based on minimum distance) are identified and mapped on GPU to be processed in parallel. …”
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A spark-based parallel fuzzy C median algorithm for web log big data
Published 2022“…Due to these factors, the data mining clustering technique is one of the most crucial tools for collecting useful data from the web. …”
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A genetic similarity algorithm for searching the Gene Ontology terms and annotating anonymous protein sequences
Published 2008“…The genetic similarity algorithm combines semantic similarity measure algorithm with parallel genetic algorithm. …”
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Parallel backpropagation neural network training for face recognition
Published 2023“…In this paper, we describe implementation of ANN training process using backpropagation learning algorithm for exploiting the high performance SIMD architecture of GPU using CUDA. …”
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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“…Results show that the GGA outperforms the simple genetic algorithm (SGA), but it still didn't match the results in the literature. …”
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