Search Results - parallel operation ((matching algorithm) OR (learning algorithm))
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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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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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Probabilistic ensemble fuzzy ARTMAP optimization using hierarchical parallel genetic algorithms
Published 2015“…This was achieved by mitigating convergence in the genetic algorithms by employing a hierarchical parallel architecture. …”
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Enhanced and effective parallel optical flow method for vehicle detection and tracking
Published 2016“…With a view to do improvements, it is proposed to develop an unique algorithm for vehicle data recognition and tracking using Parallel Optical Flow method based on Lucas-Kanade algorithm. …”
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A parallel ensemble learning model for fault detection and diagnosis of industrial machinery
Published 2023“…Accordingly, this paper proposes a new parallel ensemble model comprising hybrid machine and deep learning for undertaking FDD tasks. …”
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A study of the high-performance computing parallelism in solving complexity of meteorology data and calculations
Published 2024“…It is associated with utilizing HPC parallelism to simultaneously execute multiple tasks or operations for meteorological research. …”
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Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems
Published 2022“…Most of the currently existing intrusion detection systems (IDS) use machine learning algorithms to detect network intrusion. Machine learning algorithms have widely been adopted recently to enhance the performance of IDSs. …”
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DC-based PV-powered home energy system
Published 2017“…The controller algorithm requires also the variation range of the geographical weather parameters (irradiance and temperature) to specify the MPP which is equivalent to that operating voltage at minimum weather parameters. …”
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Neuro Symbolic Integration and Agent Based Modelling
Published 2018“…The major domain of neuro-symbolic integration is designed by the theory are usually known as deductive systems which less such elements of human reasoning as adaptation, learning and self-organisation. Meanwhile, neural networks, known as a mathematical model of neurons in the human brain, and have various abilities, and moreover, they also provide parallel computations and therefore can perform some calculations quicker than classical learning algorithms. …”
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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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Online teleoperation of writing manipulator through graphics processing unit based accelerated stereo vision
Published 2021“…These algorithms are then parallelized using Compute Unified Device Architecture CUDA C language to run on Graphics Processing Unit GPU for hardware acceleration. …”
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A modified artificial neural network (ANN) algorithm to control shunt active power filter (SAPF) for current harmonics reduction
Published 2013“…The novelty control design is an artificial neural network (ANN) adopting a modified mathematical algorithm (a modified delta rule weight-updating W-H) and a suitable alpha value (learning rate value) which determines the filters optimal operation. …”
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High efficiency RF power amplifier with closed loop system for public safety radio communications / Lokesh Anand Vijayakumaran
Published 2019“…The key point in this research work concerns the development of RF PA line up where the research introduces 3 design methodologies which is not available in current conventional 2 -way radio design. Firstly, a parallel-combined impedance matching technique is introduced where it enables the designers to develop broadband PA with actual PA device impedance. …”
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High-Speed Implementations Of Fractal Image Compression For Low And High Resolution Images
Published 2018“…Hence, it is very challenging to achieve a real-time operation especially when this algorithm is run on a general or graphic processor unit. …”
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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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Super resolution imaging using modified lanr based on separable filtering
Published 2019“…The underlying idea is to process and reconstruct information in low and high frequency sub-bands based on separable property of neighbourhood filtering to achieve fast parallel and vectorized operation, while enhancing algorithmic performance by reducing computational burden resulting from computing the weighted function of every pixel for each pixel in an image. …”
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Investigating computational thinking among primary school students in Terengganu using visual programming
Published 2022“…Quantitative approach was used to measure student’s CT skills of Flow Control, Abstraction, Parallelism, Decomposition, Synchronization, User Interactivity and Logic from their computational artifacts. …”
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