يعرض 41 - 60 نتائج من 591 نتيجة بحث عن '(( elemental rd algorithm ) OR ((( data code algorithm ) OR ( based modeling algorithm ))))', وقت الاستعلام: 0.14s تنقيح النتائج
  1. 41

    Efficient Approximate Conformance Checking Using Trie Data Structures حسب Awad, Ahmed

    منشور في 2021
    "…In this paper, we contribute a new formulation of the proxy behavior derived from a model for approximate conformance checking. By encoding the proxy behavior using a trie data structure, we obtain a logarithmically reduced search space for alignment computation compared to a set-based representation. …"
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    A cluster-based model for QoS-OLSR protocol حسب Otrok, Hadi

    منشور في 2017
    "…Four cluster-based models are derived. Simulation results show that the novel cluster-based QoS-OLSR model, based on energy and bandwidth metrics, can efficiently prolong the network lifetime, ensure QoS and decrease delay.…"
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    conferenceObject
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    A Hybrid Deep Learning Model Using CNN and K-Mean Clustering for Energy Efficient Modelling in Mobile EdgeIoT حسب Dhananjay Bisen (19482454)

    منشور في 2023
    "…This research proposed a hybrid model for energy-efficient cluster formation and a head selection (E-CFSA) algorithm based on convolutional neural networks (CNNs) and a modified k-mean clustering (MKM) method for MEC. …"
  6. 46

    Deep Learning-Based Short-Term Load Forecasting Approach in Smart Grid With Clustering and Consumption Pattern Recognition حسب Dabeeruddin Syed (16864260)

    منشور في 2021
    "…A k-Medoid based algorithm is employed for clustering whereas the forecasting models are generated for different clusters of load profiles. …"
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    Hybrid Deep Learning-based Models for Crop Yield Prediction حسب Alexandros Oikonomidis (12050497)

    منشور في 2022
    "…In this study, we developed deep learning-based models to evaluate how the underlying algorithms perform with respect to different performance criteria. …"
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    Data of simulation model for photovoltaic system's maximum power point tracking using sequential Monte Carlo algorithm حسب Odat, Alhaj-Saleh A.

    منشور في 2024
    "…The model aims to compare the performance of classical perturb and observe (P&O) algorithm, particle swarm optimization (PSO) algorithm, flower pollination algorithm (FPA), and SMC-based tracking techniques. …"
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    article
  12. 52

    Evaluation of Aerosol Optical Depth and Aerosol Models from VIIRS Retrieval Algorithms over North China Plain حسب Jun Zhu (84054)

    منشور في 2017
    "…The “MODIS-like” VIIRS data (VIIRS_ML) are being produced experimentally at NASA, from a version of the “dark-target” algorithm that is applied to MODIS. In this study, the AOD and aerosol model types from these two VIIRS retrieval algorithms over the North China Plain (NCP) are evaluated using the ground-based CE318 Sunphotometer (CE318) measurements during 2 May 2012–31 March 2014 at three sites. …"
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    Optimization of Piezoelectric Sensor-Actuator for Plate Vibration Control Using Evolutionary Computation: Modeling, Simulation and Experimentation حسب Asan G. A. Muthalif (16888818)

    منشور في 2021
    "…Both disturbance and control signal acting on the plate is created by using piezoelectric (PZT) patches. The analytical model is derived based on the Euler-Bernoulli model. …"
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    A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method حسب Amit Kumar Balyan (18288964)

    منشور في 2022
    "…To deal with the data-imbalance issue, this research develops an efficient hybrid network-based IDS model (HNIDS), which is utilized using the enhanced genetic algorithm and particle swarm optimization(EGA-PSO) and improved random forest (IRF) methods. …"
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    Distributed Tree-Based Machine Learning for Short-Term Load Forecasting With Apache Spark حسب Ameema Zainab (16864263)

    منشور في 2021
    "…The optimal value of clustering is used in this paper to cluster the data into groups to be able to reduce the computational time additionally. Multiple tree-based machine learning algorithms are tested with parallel computation to evaluate the performance with tunable parameters on a real-world dataset. …"
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