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Frontiers and trends of supply chain optimization in the age of industry 4.0: an operations research perspective
Published 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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Various Faults Classification of Industrial Application of Induction Motors Using Supervised Machine Learning: A Comprehensive Review
Published 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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The Role of Machine Learning in Diagnosing Bipolar Disorder: Scoping Review
Published 2021“…We identified different machine learning models used in the selected studies, including classification models (18, 55%), regression models (5, 16%), model-based clustering methods (2, 6%), natural language processing (1, 3%), clustering algorithms (1, 3%), and deep learning–based models (3, 9%). …”
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Deep and transfer learning for building occupancy detection: A review and comparative analysis
Published 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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An App for Navigating Patient Transportation and Acute Stroke Care in Northwestern Ontario Using Machine Learning: Retrospective Study
Published 2024“…For cases in which Ornge air services and land ambulance medical transport were both involved in a patient transport process, data were merged and time intervals of the transport journey were determined. …”
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Fast Transient Stability Assessment of Power Systems Using Optimized Temporal Convolutional Networks
Published 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
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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Short-Term Load Forecasting in Active Distribution Networks Using Forgetting Factor Adaptive Extended Kalman Filter
Published 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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Recovery of business intelligence systems
Published 2018“…The efficiency of the data recovery algorithm is substantial for e-healthcare systems. …”
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Evacuation of a highly congested urban city
Published 2017“…A case study using real population and transportation network data was tested using the proposed methodology. …”
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Structural similarity evaluation between XML documents and DTDs
Published 2007“…The automatic processing and management of XML-based data are ever more popular research issues due to the increasing abundant use of XML, especially on the Web. …”
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Multidimensional Gains for Stochastic Approximation
Published 2019“…Two algorithms are proposed: one for the case where M≥ N and the second one for the antithesis. …”
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Development of a deep learning-based group contribution framework for targeted design of ionic liquids
Published 2024“…This computational framework can expedite and improve the process of finding desirable molecular structures of IL via accurate property predictions in a data-driven manner. …”
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Anomaly Detection Based Framework for Profile Monitoring
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doctoralThesis