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- W3201999612 abstract "Forecasting is of an immense importance in energy markets, it aims to build accurate forecasting models to inspect future scenarios. It can also be used to monitor energy profiles to detect faults and other security concerns. Many tools and services have been introduced to automate the forecasting process. However, the ‘ideal’ tool highly depends on how much it perfectly fulfills the desired behavior in the targeted application. In this paper, we introduce a configurable energy forecasting tool, which extends a set of machine learning models to provide dynamic energy forecasting services. The developed tool aims mainly to predict energy generation/consumption, build forecasting models, compare predictions, and fine-tune prediction models. Then, we utilize this tool to conduct two case studies. The first aims to compare the performance of different prediction models in residential and office buildings, using multiple experiments with variations of input fields. The second one investigates the role of the energy forecasting tool to raise awareness regarding security incidents in a shop floor. Results from both case studies emphasized the prospective role of the developed tool in energy forecasting and security awareness." @default.
- W3201999612 created "2021-10-11" @default.
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- W3201999612 date "2021-01-01" @default.
- W3201999612 modified "2023-10-16" @default.
- W3201999612 title "Intelligence as a Service: A Tool for Energy Forecasting and Security Awareness" @default.
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- W3201999612 doi "https://doi.org/10.1007/978-3-030-85710-3_15" @default.
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