يعرض 301 - 320 نتائج من 409 نتيجة بحث عن '(( element method algorithm ) OR ((( data processing algorithm ) OR ( based location algorithm ))))', وقت الاستعلام: 0.12s تنقيح النتائج
  1. 301

    Detecting and Predicting Archaeological Sites Using Remote Sensing and Machine Learning—Application to the Saruq Al-Hadid Site, Dubai, UAE حسب Ben-Romdhane, Haïfa

    منشور في 2023
    "…The modelling and prediction accuracies are expected to improve with the insertion of a neural network and backpropagation algorithms based on the performed cluster groups following more recent field surveys. …"
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    article
  2. 302
  3. 303

    Optimum Track to Track Fusion Using CMA-ES and LSTM Techniques حسب Fares, Samar

    منشور في 2024
    "…The sensors are unbiased radars with fixed locations. The first method uses an offline technique based on a global optimizer called the CMA-ES algorithm and the second one uses LSTM in its different forms to learn the online adjustment of the fusion weights between the two tracks. …"
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  4. 304

    High-order parametrization of the hypergeometric-Meijer approximants حسب Abouzeid M. Shalaby (16329062)

    منشور في 2023
    "…<p>In this work, we introduce an extension to the hypergeometric algorithm we developed before for the resummation of divergent series.The extension overcome the time-consuming problem we face in the parametrization process of the hypergeometric approximants. …"
  5. 305

    UAV Trajectory Planning for Data Collection from Time-Constrained IoT Devices حسب Samir, Moataz

    منشور في 2019
    "…Then, we develop an effective sub-optimal algorithm based on successive convex approximation in order to obtain results for larger network scenarios. …"
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    article
  6. 306

    Applying urban parametric design optimisation processes to a hot climate: Case study of the UAE حسب Taleb, Hanan

    منشور في 2014
    "…An urban area in Dubai was selected to act as the case study location for this project. An in-depth analysis was carried out between the base case and the optimised case. …"
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  7. 307

    Student advising decision to predict student's future GPA based on Genetic Fuzzimetric Technique (GFT) حسب Kouatli, Issam

    منشور في 2015
    "…Decision making and/or Decision Support Systems (DSS) using intelligent techniques like Genetic Algorithm and fuzzy logic is becoming popular in many new applications. …"
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    conferenceObject
  8. 308

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

    منشور في 2022
    "…The two main steps in HLS are: operations scheduling and data-path allocation. In this work, we present a resource constrained scheduling approach that minimizes latency and subject to resource constraints using a deep Q learning algorithm. …"
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    masterThesis
  9. 309

    A Novel Encryption Method for Dorsal Hand Vein Images on a Microcomputer حسب M. Z. Yildiz (16855476)

    منشور في 2019
    "…Second, the pre- and post-processed images were encrypted with a new encryption algorithm in the microcomputer environment. …"
  10. 310

    The Role of Artificial Intelligence in Decoding Speech from EEG Signals: A Scoping Review حسب Uzair Shah (15740699)

    منشور في 2022
    "…The study selection process was carried out in three phases: study identification, study selection, and data extraction. …"
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    Benchmark on a large cohort for sleep-wake classification with machine learning techniques حسب Joao Palotti (8479842)

    منشور في 2019
    "…However, the largest experiments conducted to date, have had only hundreds of participants. In this work, we processed the data of the recently published Multi-Ethnic Study of Atherosclerosis (MESA) Sleep study to have both PSG and actigraphy data synchronized. …"
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    An Improved Genghis Khan Optimizer based on Enhanced Solution Quality Strategy for Global Optimization and Feature Selection Problems حسب Abdel-Salam, Mahmoud

    منشور في 2024
    "…Feature selection (FS) is the activity of defining the most contributing feature subset among all used features to improve the superiority of datasets with a large number of dimensions by selecting significant features and eliminating redundant and irrelevant ones. Therefore, this process can be seen as an optimization process. The primary goals of feature selection are to decrease the number of dimensions and enhance classification accuracy in many domains, such as text classification, large-scale data analysis, and pattern recognition. …"
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  15. 315
  16. 316

    A Survey of Deep Learning Approaches for the Monitoring and Classification of Seagrass حسب Uzma Nawaz (21980708)

    منشور في 2025
    "…By synthesizing findings across various data sources and model architectures, we offer critical insights into the selection of context-aware algorithms and identify key research gaps, an essential step for advancing the reliability and applicability of AI-driven seagrass conservation efforts.…"
  17. 317

    The bus sightseeing problem حسب Qian Hu (205735)

    منشور في 2023
    "…A mixed-integer programming formulation for the BSP is provided and solved by a Benders decomposition algorithm. For large-scale instances, an iterated local search based metaheuristic algorithm is developed with some tailored neighborhood operators. …"
  18. 318

    Identification of the Uncertainty Structure to Estimate the Acoustic Release of Chemotherapeutics From Polymeric Micelles حسب Wadi, Ali

    منشور في 2017
    "…The identified a priori knowledge is used to implement an optimal Kalman filter, a multi-hypothesis Kalman filter, and a variant of the full information estimator (moving horizon estimator) to the problem at hand. The proposed algorithms are initially deployed in a simulation environment, and then the experimental data sets are fed into the algorithms to validate their performance. …"
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    article
  19. 319

    Lagrangian tracking in stochastic fields with application to an ensemble of velocity fields in the Red Sea حسب Issa, Leila

    منشور في 2018
    "…Lagrangian tracking of passive tracers in a stochastic velocity field within a sequential ensemble data assimilation framework is challenging due to the exponential growth in the number of particles. …"
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    article
  20. 320