يعرض 1 - 20 نتائج من 256 نتيجة بحث عن '(((( elements method algorithm ) OR ( models testing algorithm ))) OR ( neural coding algorithm ))*', وقت الاستعلام: 0.13s تنقيح النتائج
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    Metaheuristic Algorithm for State-Based Software Testing حسب Haraty, Ramzi A.

    منشور في 2018
    "…This article presents a metaheuristic algorithm for testing software, especially web applications, which can be modeled as a state transition diagram. …"
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    article
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    A reduced model for phase-change problems with radiation using simplified PN approximations حسب Belhamadia, Youssef

    منشور في 2025
    "…The performance of the proposed reduced models is analyzed on several test examples for coupled radiative heat transfer and phase-change problems in two and three space dimensions. …"
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    article
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    Modeling and automated blackbox regression testing of web applications حسب Haraty, Ramzi

    منشور في 2008
    "…Having discovered, as well, that there is no automated black box regression testing technique, we also propose a methodology and algorithm to create a tool capable of applying black box regression testing automatically…"
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    article
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    New fault models and efficient BIST algorithms for dual-portmemories حسب Amin, A.A.

    منشور في 1997
    "…New fault models are proposed, and efficient O(n) test algorithms are described for both the memory array and the address decoders. …"
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    article
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    Enhancing Breast Cancer Diagnosis With Bidirectional Recurrent Neural Networks: A Novel Approach for Histopathological Image Multi-Classification حسب Rajendra Babu Chikkala (22330876)

    منشور في 2025
    "…<p dir="ltr">In recent years, deep learning methods have dramatically improved medical image analysis, though earlier models faced difficulties in capturing intricate spatial and contextual details. …"
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    Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks حسب Najam Us Sahar Riyaz (22927843)

    منشور في 2025
    "…At the same time, virtual sample augmentation and genetic algorithm feature selection elevate sparse data performance, raising k-nearest neighbor models from R<sup>2</sup> = 0.05 to 0.99 in a representative thiophene set. …"