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Full-Text Articles in Computer Engineering
Online/Incremental Learning To Mitigate Concept Drift In Network Traffic Classification, Alberto R. De La Rosa
Online/Incremental Learning To Mitigate Concept Drift In Network Traffic Classification, Alberto R. De La Rosa
Open Access Theses & Dissertations
Communication networks play a large role in our everyday lives. COVID19 pandemic in 2020 highlighted their importance as most jobs had to be moved to remote work environments. It is possible that the spread of the virus, the death toll, and the economic consequences would have been much worse without communication networks. To remove sole dependence on one equipment vendor, networks are heterogeneous by design. Due to this, as well as their increasing size, network management has become overwhelming for network managers. For this reason, automating network management will have a significant positive impact. Machine learning and software defined networking …
Deep Learning For Load Forecasting With Smart Meter Data: Online And Federated Learning, Mohammad Navid Fekri
Deep Learning For Load Forecasting With Smart Meter Data: Online And Federated Learning, Mohammad Navid Fekri
Electronic Thesis and Dissertation Repository
Electricity load forecasting has been attracting increasing attention because of its importance for energy management, infrastructure planning, and budgeting. In recent years, the proliferation of smart meters has created new opportunities for forecasting on the building and even individual household levels. Machine learning (ML) has achieved great successes in this domain; however, conventional ML techniques require data transfer to a centralized location for model training, therefore, increasing network traffic and exposing data to privacy and security risks. Also, traditional approaches employ offline learning, which means that they are only trained once and miss out on the possibility to learn from …