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coding algorithm » cosine algorithm (Expand Search), colony algorithm (Expand Search), scheduling algorithm (Expand Search)
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search » research (Expand Search)
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121
An Ultrafast Maximum Power Point Setting Scheme for Photovoltaic Arrays Using Model Parameter Identification
Published 2015“…In order to separate the search algorithms from converter operation, a model parameter identification approach is presented to estimate insolation conditions of each PV panel and build a real-time overallP-Icurve of PV arrays. …”
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Distributed Tree-Based Machine Learning for Short-Term Load Forecasting With Apache Spark
Published 2021“…One thousand distribution transformers' real data from Spain for three years are used to demonstrate the performance of the proposed methodology with a trade-off between accuracy and processing time.</p><h2>Other Information</h2><p>Published in: IEEE Access<br>License: <a href="https://creativecommons.org/licenses/by/4.0/legalcode" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/access.2021.3072609" target="_blank">https://dx.doi.org/10.1109/access.2021.3072609</a></p>…”
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Random Forest Bagging and X‐Means Clustered Antipattern Detection from SQL Query Log for Accessing Secure Mobile Data
Published 2021“…The results revealed that the RFBXSQLQC technique outperforms the existing algorithms by 19% with pattern detection accuracy, 34% minimized time complexity, 64% false-positive rate, and 31% in terms of computational overhead.…”
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Multi-Agent Meta Reinforcement Learning for Reliable and Low-Latency Distributed Inference in Resource-Constrained UAV Swarms
Published 2025“…A key requirement in these applications is minimizing the latency of data processing, particularly for time-sensitive tasks like image classification of IIoT device data. …”
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126
Enhancing Healthcare Systems With Deep Reinforcement Learning: Insights Into D2D Communications and Remote Monitoring
Published 2024“…The core of DRLLVT is its novel algorithm that leverages Deep Reinforcement Learning (DRL) to dynamically adapt to changing environmental conditions, facilitating real-time decisions that consider node capacities, latency, and the overall network dynamics. …”
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Deep Learning-Based Short-Term Load Forecasting Approach in Smart Grid With Clustering and Consumption Pattern Recognition
Published 2021“…The proposed approach delivers an improvement of around 44% in training time while maintaining accuracy using single-core processing as compared to non-clustering models.…”
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131
Estimating Vehicle State by GPS/IMU Fusion with Vehicle Dynamics
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132
Combining offline and on-the-fly disambiguation to perform semantic-aware XML querying
Published 2023“…Many efforts have been deployed by the IR community to extend freetext query processing toward semi-structured XML search. Most methods rely on the concept of Lowest Comment Ancestor (LCA) between two or multiple structural nodes to identify the most specific XML elements containing query keywords posted by the user. …”
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133
Mapping realistic data sets on parallel computers
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GENETIC SCHEDULING OF TASK GRAPHS
Published 2020“…The problem of assigning tasks to processing elements as a combinatorital optimization is formulated, and a heuristic based on a genetic algorithm is presented. …”
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135
Localization of Damages in Plain And Riveted Aluminium Specimens using Lamb Waves
Published 2018“…The TOA data of the wave reflected from the damage is used in the two arrival time difference and astroid algorithms to locate the damage in an enclosed area. …”
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Mobile Robot Navigation in Dynamic Environments Using an Improved RRT* Approach
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Bridge Structural Health Monitoring Using Mobile Sensor Networks
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Resources Allocation for Drones Tracking Utilizing Agent-Based Proximity Policy Optimization
Published 2023“…The learned system can apply sensor allocation online, works in real-time, and selects one radar and one camera at a time without having to reevaluate a cost function at every time step. …”
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140
Vehicular-OBUs-As-On-Demand-Fogs
Published 2020“…Observing the headway in vehicular industry, new applications are developed demanding more resources. For instance, real-time vehicular applications require fast processing of the vast amount of generated data by vehicles in order to maintain service availability and reachability while driving. …”
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