Search Results - (( time estimation method algorithm ) OR ( parallel localization based algorithm ))
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An approximate method for solving unsteady transitional and rarefied flow regimes in pulsed pressure chemical vapor deposition process using the quiet direct simulation method
Published 2023“…In QDS, the molecular velocity is represented by the Maxwell-Boltzmann equilibrium distribution approximated by a Gauss-Hermite quadrature. The QDS algorithm is suitable for parallelization with its highly local nature. …”
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Effective software fault localization based on complex network theory / Abubakar Zakari
Published 2019“…Furthermore, two novel fault localization techniques based on complex network theory, namely multiple fault localization based on complex network theory (FLCN-M) and single fault localization based on complex network theory (FLCN-S), are proposed to improve localization effectiveness, and to aid developers’ to localize multiple faults simultaneously in a single diagnosis rank list. …”
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Hybridizing guided genetic algorithm and single-based metaheuristics to solve unrelated parallel machine scheduling problem with scarce resources
Published 2023“…The single-based metaheuristics replaces the mutation in the genetic algorithm. …”
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Semiparametric inference procedure for the accelarated failure time model with interval-censored data
Published 2019“…The rank-based methods, estimating algorithms, and resampling techniques that are developed do not involve the difficulties of the existing estimating procedures. …”
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Workflow optimization in distributed computing environment for stream-based data processing model / Saima Gulzar Ahmad
Published 2017“…Similarly, when data parallelism is introduced in the algorithm the performance of the algorithm improved further by 12% in latency and 17% in throughput when compared to PDWA algorithm. …”
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PMT : opposition based learning technique for enhancing metaheuristic algorithms performance
Published 2020“…In some complex problems, the convergence rate can still be poor owing to becoming trapped in local optima. Opposition-based learning (OBL) has shown promising results to address the aforementioned issue. …”
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Hybrid FFT-ADALINE algorithm with fast estimation of harmonics in power system
Published 2016“…In the proposed method, both of the aforementioned algorithms are combined for harmonic estimation where it is able to respond immediately to any change of the measured harmonics and the settling time is reduced to half cycle of the measurement signal. …”
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PMT: opposition-based learning technique for enhancing meta-heuristic performance
Published 2019“…In some complex problems, the convergence rate can still be poor owing to becoming trapped in local optima. Addressing these issues, this research proposes a new general opposition-based learning (OBL) technique inspired by a natural phenomenon of parallel mirrors systems called the parallel mirrors technique (PMT). …”
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Design and analysis of management platform based on financial big data
Published 2023“…In addition, a financial data management platform based on distributed Hadoop architecture is designed, which combines MapReduce framework with the fuzzy clustering algorithm and the local outlier factor (LOF) algorithm, and uses MapReduce to operate in parallel with the two algorithms, thus improving the performance of the algorithm and the accuracy of the algorithm, and helping to improve the operational efficiency of enterprise financial data processing. …”
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Grid-based simultaneous localization and mapping using Rao-blackwellized particle filter with neural network for mini robots / Norhidayah Mohamad Yatim
Published 2018“…In this research, to enable mini robots to operate in various environment, OG map with SLAM or grid-based SLAM algorithm was developed. Previous works in this domain had to assume for all walls in the environment are either parallel or perpendicular to each other.…”
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Fast adaptive motion estimation search algorithm for H.264 encoder
Published 2012“…Furthermore this study presents an analysis of the performance of the proposed algorithm in terms of motion estimation time, total encoding time, video quality (PSNR), and bit rate. …”
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An enhanced segment particle swarm optimization algorithm for kinetic parameters estimation of the main metabolic model of Escherichia coli
Published 2020“…The results revealed that the proposed method had the ability to deal with kinetic parameters estimation in terms of time consumption and distance minimization.…”
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A parallel ensemble learning model for fault detection and diagnosis of industrial machinery
Published 2023“…The base learners adopt a hybrid Back-Propagation (BP) and Particle Swarm Optimization (PSO) algorithms to exploit the corresponding local and global optimization capabilities for identifying optimal features and improving FDD performance. …”
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Distributed parallel deep learning with a hybrid backpropagation-particle swarm optimization for community detection in large complex networks
Published 2022“…In this paper, a parallel deep learning-based community detection method in large complex networks (CNs) is proposed. …”
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Travel-Time Estimation By Cubic Hermite Curve
Published 2022“…This comparison demonstrated that the proposed method estimates travel time more accurately than Google Maps and Waze. …”
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Performance Enhancement of Routing Protocols in Mobile Wireless Ad-Hoc Networks Using Fuzzy Reasoning Algorithm
Published 2006“…In the first method, the fuzzy reasoning is used to estimate the time route can stay active in the routing table. …”
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