يعرض 1 - 20 نتائج من 96 نتيجة بحث عن '(((( path finding algorithm ) OR ( spatial modeling algorithm ))) OR ( relevant data algorithm ))', وقت الاستعلام: 0.12s تنقيح النتائج
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    Spatially-Distributed Missions With Heterogeneous Multi-Robot Teams حسب Eduardo Feo-Flushing (23276023)

    منشور في 2021
    "…Both combine a generic MILP solver and a genetic algorithm, resulting in efficient anytime algorithms. …"
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    CoLoSSI: Multi-Robot Task Allocation in Spatially-Distributed and Communication Restricted Environments حسب Ishaq Ansari (22047902)

    منشور في 2024
    "…<p dir="ltr">In our research, we address the problem of coordination and planning in heterogeneous multi-robot systems for missions that consist of spatially localized tasks. Conventionally, this problem has been framed as a task allocation problem that maps tasks to robots. …"
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    Variable Selection in Data Analysis: A Synthetic Data Toolkit حسب Mitra, Rohan

    منشور في 2024
    "…Variable (feature) selection plays an important role in data analysis and mathematical modeling. This paper aims to address the significant lack of formal evaluation benchmarks for feature selection algorithms (FSAs). …"
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    article
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    Data Generation for Path Testing حسب Mansour, Nashat

    منشور في 2004
    "…We present two stochastic search algorithms for generating test cases that execute specified paths in a program. …"
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    article
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    UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional data حسب Behrouz Ahadzadeh (19757022)

    منشور في 2024
    "…UniBFS exploits the inherent characteristic of binary algorithms-binary coding-to search the entire problem space for identifying relevant features while avoiding irrelevant ones. …"
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    Auto-indexing Arabic texts based on association rule data mining. (c2015) حسب Rouba G. Nasrallah

    منشور في 2015
    "…Our model denotes extracting new relevant words by relating those chosen by the previous classical methods, to new words using data mining rules. …"
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    masterThesis
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    STEM: spatial speech separation using twin-delayed DDPG reinforcement learning and expectation maximization حسب Muhammad Salman Khan (7202543)

    منشور في 2025
    "…In this paper, a novel speech separation algorithm is proposed that integrates the twin-delayed deep deterministic (TD3) policy gradient reinforcement learning (RL) agent with the expectation maximization (EM) algorithm for clustering the spatial cues of individual sources separated on azimuth. …"
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    DRL-Based UAV Path Planning for Coverage Hole Avoidance: Energy Consumption and Outage Time Minimization Trade-Offs حسب Bahareh Jafari (22501715)

    منشور في 2025
    "…By deploying a deep reinforcement learning algorithm, we find optimal UAV paths based on the two families of trajectories: spiral and oval curves, to tackle different design considerations and constraints, in terms of QoS, energy consumption and coverage hole avoidance. …"
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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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    Optimizing Document Classification: Unleashing the Power of Genetic Algorithms حسب Ghulam Mustafa (458105)

    منشور في 2023
    "…Additionally, our proposed model optimizes the features using a genetic algorithm. Optimal feature selection performances a crucial role in this domain, enhancing the overall accuracy of the document classification system while reducing the time complexity associated with selecting the most relevant features from this large-dimensional space. …"
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    Indexing Arabic texts using association rule data mining حسب Haraty, Ramzi A.

    منشور في 2019
    "…The model denotes extracting new relevant words by relating those chosen by previous classical methods to new words using data mining rules. …"
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    article
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    MLMRS-Net: Electroencephalography (EEG) motion artifacts removal using a multi-layer multi-resolution spatially pooled 1D signal reconstruction network حسب Sakib Mahmud (15302404)

    منشور في 2022
    "…Because the diagnosis of many neurological diseases is heavily reliant on clean EEG data, it is critical to eliminate motion artifacts from motion-corrupted EEG signals using reliable and robust algorithms. Although a few deep learning-based models have been proposed for the removal of ocular, muscle, and cardiac artifacts from EEG data to the best of our knowledge, there is no attempt has been made in removing motion artifacts from motion-corrupted EEG signals: In this paper, a novel 1D convolutional neural network (CNN) called multi-layer multi-resolution spatially pooled (MLMRS) network for signal reconstruction is proposed for EEG motion artifact removal. …"