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Showing 441 - 460 results of 656 for search '(((( data mining algorithm ) OR ( problem using algorithm ))) OR ( element method algorithm ))', query time: 0.10s Refine Results
  1. 441

    An Evolutionary Meta-Heuristic for State Justification in Sequential Automatic Test Pattern Generation by El-Maleh, Aiman H.

    Published 2001
    “…A common search optimization in sequential ATPG is to justify a desired state assignment on the sequential elements. State justification using deterministic algorithms is a difficult problem and is prone to many backtracks, which can lead to high execution times. …”
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    article
  2. 442

    An evolutionary meta-heuristic for state justification insequential automatic test pattern generation by El-Maleh, A.H.

    Published 2001
    “…A common search operation in sequential ATPG is to justify a desired state assignment on the sequential elements. State justification using deterministic algorithms is a difficult problem and is prone to many backtracks, which can lead to high execution times. …”
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    article
  3. 443

    Deep Reinforcement Learning for Resource Constrained HLS Scheduling by Makhoul, Rim

    Published 2022
    “…In this work, we present a resource constrained scheduling approach that minimizes latency and subject to resource constraints using a deep Q learning algorithm. The actions and rewards for the proposed algorithm are selected carefully to guide the agent to its objective. …”
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    masterThesis
  4. 444

    Fast force-directed/simulated evolution hybrid for multiobjective VLSI cell placement by Sait, Sadiq M.

    Published 2004
    “…In this work, a fast hybrid algorithm is designed to address this problem. The algorithm employs simulated evolution (SE), an iterative search heuristic that comprises three steps: evaluation, selection and allocation. …”
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    article
  5. 445

    Reliability and fault tolerance based topological optimization of computer networks - part I: enumerative techniques by Abd-El-Barr, Mostafa

    Published 2003
    “…Experimental results obtained from a set of randomly generated networks using the proposed algorithms are presented and compared to those obtained using existing techniques. …”
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    article
  6. 446

    Faces in the crowd by Abu-Khzam, Faisal N.

    Published 2017
    “…We show how to obtain an outerplanar subgraph of a graph of disk dimension k by removing at most 2k − 2 vertices. We use this reduction technique to obtain a tree-decomposition of width at most 2k and a linear-time 3-approximation algorithm for the pathwidth problem on graphs of fixed disk dimension. …”
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    conferenceObject
  7. 447

    Could Petrol Stations Play a Key Role in Transportation Electrification? A GIS-Based Coverage Maximization of Fast EV Chargers in Urban Environment by Safak Bayram (16925975)

    Published 2022
    “…The spatial optimization problem is solved using a linear-programming relaxation based MCLP algorithm developed in Python. …”
  8. 448
  9. 449

    Assessing the potential of network reconfiguration to improve distributed generation hosting capacity in active distribution systems by Margossian, Harag

    Published 2014
    “…This work further proposes an algorithm to break-down the large problem size when many periods have to be considered. …”
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    article
  10. 450

    GenDE: A CRF-Based Data Extractor by Kayed, Mohammed

    Published 2020
    “…It verifies the site schema and extracts data from the Web pages using Conditional Random Fields (CRFs). The problem is solved by breaking down an observation sequence (a Web page) into simpler subsequences that will be labeled using CRF. …”
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  11. 451
  12. 452

    Uplink Noma in UAV-Assisted IoT Networks by Mrad, Ali

    Published 2022
    “…The second device is then selected using a heuristic algorithm based on prioritizing devices with higher bit rate requirements and strict deadlines. …”
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    masterThesis
  13. 453

    A forward-backward Kalman for the estimation of time-variant channels in OFDM by Al-Naffouri, T.Y.

    Published 2005
    “…In this paper, we propose an expectation-maximization (EM) algorithm for joint channel and data recovery. The algorithm makes use of the rich structure of the underlying communication problem-a structure induced by the data and channel constraints. …”
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    article
  14. 454

    Parallel tabu search in a heterogeneous environment by Al-Yamani, A.

    Published 2003
    “…The multiobjective nature of this problem is addressed using a fuzzy goal-based cost computation.…”
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    article
  15. 455

    Identification of physically based models of residential air-conditioners for direct load control management by El-Ferik, S.

    Published 2004
    “…In this work, we address the problem of identifying the parameters of an aggregated elemental model representing a housing unit with an A/C system. …”
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    article
  16. 456

    Protein structure prediction in the 3D HP model by Abu-Khzam, Faisal

    Published 2009
    “…To test our algorithm, we use two sets of benchmark sequences of different lengths. …”
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    conferenceObject
  17. 457

    Data Generation for Path Testing by Mansour, Nashat

    Published 2004
    “…These algorithms are based on an optimization formulation of the path testing problem which include both integer- and real-value test cases. …”
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    article
  18. 458
  19. 459

    FAST FUZZY FORCE-DIRECTED/SIMULATED EVOLUTION METAHEURISTIC FOR MULTIOBJECTIVE VLSI CELL PLACEMENT by Sait, Sadiq M.

    Published 2006
    “…VLSI standard cell placement is the process of arranging circuit components (modules) on a silicon layout. The cell placement problem is a proven NP hard combinatorial optimization problem. …”
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    article
  20. 460

    An enhanced binary Rat Swarm Optimizer based on local-best concepts of PSO and collaborative crossover operators for feature selection by Abu Zitar, Raed

    Published 2022
    “…In this paper, an enhanced binary version of the Rat Swarm Optimizer (RSO) is proposed to deal with Feature Selection (FS) problems. FS is an important data reduction step in data mining which finds the most representative features from the entire data. …”