بدائل البحث:
processing algorithm » processing algorithms (توسيع البحث)
setting algorithm » scheduling algorithm (توسيع البحث)
rd algorithm » _ algorithms (توسيع البحث)
elementi rd » elementi per (توسيع البحث)
processing algorithm » processing algorithms (توسيع البحث)
setting algorithm » scheduling algorithm (توسيع البحث)
rd algorithm » _ algorithms (توسيع البحث)
elementi rd » elementi per (توسيع البحث)
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Digital twin in energy industry: Proposed robust digital twin for power plant and other complex capital-intensive large engineering systems
منشور في 2022"…Data-driven algorithms with capabilities to predict the system’s dynamic behavior still need to be developed. …"
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Multi Agent Reinforcement Learning Approach for Autonomous Fleet Management
منشور في 2019احصل على النص الكامل
doctoralThesis -
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Artificial Intelligence Driven Smart Farming for Accurate Detection of Potato Diseases: A Systematic Review
منشور في 2024"…It has been learned that image-processing techniques overwhelm the existing research and have the potential to integrate meteorological data. …"
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207
A Novel Partitioned Random Forest Method-Based Facial Emotion Recognition
منشور في 2025"…The proposed method divides multiple regions (different data lengths) into the feature space, allowing the algorithm to learn more complex decision boundaries. …"
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Various Faults Classification of Industrial Application of Induction Motors Using Supervised Machine Learning: A Comprehensive Review
منشور في 2025"…In current literature, there are a number of papers that address all these faults using different methods, and this paper compiles the information from the written works for ease of access. Machine learning algorithms are a set of data-driven rules that are able to classify specific faults in induction motors, which will be explained further in this review paper. …"
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211
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Frontiers and trends of supply chain optimization in the age of industry 4.0: an operations research perspective
منشور في 2024"…It contributes to the literature by identifying the four OR innovations to typify the recent advances in SC optimization: new modeling conditions, new inputs, new decisions, and new algorithms. Furthermore, we recommend four promising research avenues in this interplay: (1) incorporating new decisions relevant to data-enabled SC decisions, (2) developing data-enabled modeling approaches, (3) preprocessing parameters, and (4) developing data-enabled algorithms. …"
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213
Machine Learning–Based Approach for Identifying Research Gaps: COVID-19 as a Case Study
منشور في 2024"…</p><h3>Methods</h3><p dir="ltr">We conducted an analysis to identify research gaps in COVID-19 literature using the COVID-19 Open Research (CORD-19) data set, which comprises 1,121,433 papers related to the COVID-19 pandemic. …"
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Deep and transfer learning for building occupancy detection: A review and comparative analysis
منشور في 2022"…This work investigates occupancy detection methods to develop an efficient system for processing sensor data while providing accurate occupancy information. …"
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Fast Transient Stability Assessment of Power Systems Using Optimized Temporal Convolutional Networks
منشور في 2024"…The proposed algorithm unlocks scalability and system adaptability to operational variability by adopting numeric imputation and missing-data-tolerant techniques. …"
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Multi-Agent Meta Reinforcement Learning for Reliable and Low-Latency Distributed Inference in Resource-Constrained UAV Swarms
منشور في 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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218
Short-Term Load Forecasting in Active Distribution Networks Using Forgetting Factor Adaptive Extended Kalman Filter
منشور في 2023"…A few research studies focused on developing data filtering algorithm for the load forecasting process using approaches such as Kalman filter, which has good tracking capability in the presence of noise in the data collection process. …"
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Optimizing ADWIN for Steady Streams
منشور في 2022"…However, online machine learning comes with many challenges for the different aspects of the learning process, starting from the algorithm design to the evaluation method. …"
احصل على النص الكامل
احصل على النص الكامل
احصل على النص الكامل
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Lagrangian tracking in stochastic fields with application to an ensemble of velocity fields in the Red Sea
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. …"
احصل على النص الكامل
احصل على النص الكامل
احصل على النص الكامل
احصل على النص الكامل
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