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يعرض 81 - 100 نتائج من 204 نتيجة بحث عن '(( algorithm machine function ) OR ( ((algorithm where) OR (algorithm model)) function ))', وقت الاستعلام: 0.13s تنقيح النتائج
  1. 81

    A systolic algorithm for VLSI design of a 1/N rate Viterbi decoder حسب Sait, Sadiq M.

    منشور في 1989
    "…The second consists of a matrix of simpler processors which update survived paths and provide the decoded output. The systolic algorithm is modeled in AHPL to verify functional correctness. …"
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    article
  2. 82

    Scatter search for homology modeling حسب Mansour, Nashat

    منشور في 2016
    "…Results obtained by our SS algorithm are compared with other approaches. The 3D models predicted by our algorithm show improved root mean standard deviations with respect to the native structures.…"
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    conferenceObject
  3. 83

    Gas pipeline modelling and control حسب Whalley, R

    منشور في 2015
    "…The distributed parameter modelling of the gas flow through long pipelines is considered. …"
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  4. 84

    Rigorous Phase Equilibrium Calculation Methods for Strong Electrolyte Solutions: The Isothermal Flash حسب Ilias K. Nikolaidis (9217172)

    منشور في 2022
    "…In this way, an augmented function (Lagrange function) is formulated which serves as the basis for the equations that govern phase equilibrium. …"
  5. 85
  6. 86

    Modeling of magnetization curves for computer-aided design حسب Abuelma’atti, M.T.

    منشور في 1993
    "…A simple algorithm is presented for obtaining the coefficients of the sine-series function for modelling the magnetization curves of magnetic materials. …"
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    article
  7. 87

    DeepRaman: Implementing surface-enhanced Raman scattering together with cutting-edge machine learning for the differentiation and classification of bacterial endotoxins حسب Samir Brahim, Belhaouari

    منشور في 2025
    "…ResultMost traditional machine learning algorithms achieved distinction accuracies of over 99 percent, whereas DeepRaman demonstrated an exceptional accuracy of 100 percent. …"
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  8. 88
  9. 89

    Wiener-Hammerstein Model Identification-Recursive lgorithms حسب Emara-Shabaik, Husam

    منشور في 2020
    "…Recursive algorithms for parameter estimation of Wiener-Hammerstein (W-H)models are developed. …"
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    article
  10. 90
  11. 91

    An efficient failure-resilient mutual exclusion algorithm for distributed systems leveraging a novel zero-message overlay structure حسب Mouna Rabhi (17086969)

    منشور في 2024
    "…An extensive simulation study demonstrates the viability and efficiency of the proposed algorithm under various node failure models, and relevant metrics (e.g., node queue dimension, number of exchanged messages, and number of disconnected nodes) indicate a graceful degradation in performance with decreasing number of functioning nodes. …"
  12. 92

    High-Accurate Parameter Identification of PEMFC Using Advanced Multi-Trial Vector-Based Sine Cosine Meta-Heuristic Algorithm حسب Badreddine Kanouni (23073244)

    منشور في 2025
    "…The trigonometric function-based sine cosine algorithm (SCA) may solve such problems, but it traps in local optima, making it inappropriate for larger optimization tasks. …"
  13. 93

    Optimum sensors allocation for drones multi-target tracking under complex environment using improved prairie dog optimization حسب Abu Zitar, Raed

    منشور في 2024
    "…The Extended Kalman Filter (EKF) is used for state estimation with proper clutter and detection models. Since we use Multi-objects to track, the Joint Probability Distribution Function (JPDA) estimates the best measurement values with a preset gating threshold. …"
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  14. 94

    ANT-colony optimization-direct torque control for a doubly fed induction motor : An experimental validation حسب Said Mahfoud (17150968)

    منشور في 2022
    "…The best solutions adopted in this situation are often based on optimization algorithms that generate the controller’s gains in each period where there is an internal or external perturbation, adapting the behaviors of the PID against the system’s nonlinearity. …"
  15. 95

    Oversampling techniques for imbalanced data in regression حسب Samir Brahim Belhaouari (9427347)

    منشور في 2024
    "…This success rate is determined by the frequency of instances where models performed better when augmented data was used compared to instances with no augmentation. …"
  16. 96

    A hybrid of clustering and meta-heuristic algorithms to solve a p-mobile hub location–allocation problem with the depreciation cost of hub facilities حسب Mahdi Mokhtarzadeh (11593310)

    منشور في 2021
    "…A multi-objective mixed-integer non-linear programming (MINLP) model is developed. To solve the proposed model, four meta-heuristic algorithms, namely multi-objective particle swarm optimization (MOPSO), a non-dominated sorting genetic algorithm (NSGA-II), a hybrid of k-medoids as a famous clustering algorithm and NSGA-II (KNSGA-II), and a hybrid of K-medoids and MOPSO (KMOPSO) are implemented. …"
  17. 97

    Modelling Exchange Rates during Currency Crisis using Neural Networks حسب Nasr, G. E.

    منشور في 2006
    "…Exchange rate data from the Lebanese currency crisis period of 1985-1992 is used for training, testing and evaluation of the models. Forecasting performance measures represented by well established error functions are presented for the three models. …"
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  18. 98

    Large language models for code completion: A systematic literature review حسب Rasha Ahmad Husein (19744756)

    منشور في 2024
    "…This is achieved by predicting subsequent tokens, such as keywords, variable names, types, function names, operators, and more. Different techniques can achieve code completion, and recent research has focused on Deep Learning methods, particularly Large Language Models (LLMs) utilizing Transformer algorithms. …"
  19. 99

    Integrated Energy Optimization and Stability Control Using Deep Reinforcement Learning for an All-Wheel-Drive Electric Vehicle حسب Reza Jafari (3494018)

    منشور في 2025
    "…A tailored multi-term reward function is structured to penalize excessive yaw rate error, sideslip angle, tire slip deviations beyond peak grip regions, and power losses based on a realistic electric machine efficiency map. …"
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