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Arctic coastal morphology is increasingly affected by changes to the climate. As the season length for shorefast ice decreases and temperatures warm permafrost, coastlines are increasingly susceptible to erosion from storm waves. Such coastal erosion is significant since the majority of the population centers and infrastructure in the Arctic are located near the coasts. Stakeholders and decision makers...
How to operate a BFG/coal co-firing boiler in high efficiency is challenging for a gas/solid multi-fuel combustion system. Taking operation data from a real boiler, this study proposes an operation optimization strategy of BFG/coal co-firing boiler based on deep learning. Firstly, the thermal efficiency model is constructed based on deep learning with all the actual sampling data, which outperform...
Feature engineering involves constructing novel features from given data with the goal of improving predictive learning performance. Feature engineering is predominantly a human-intensive and time consuming step that is central to the data science workflow. In this paper, we present a novel system called "Cognito", that performs automatic feature engineering on a given dataset for supervised...
In this paper, models are created to predict the levels of ground level Ozone at particular locations based on the cross-correlation and spatial-correlation of different air pollutants whose readings are obtained from several different air quality monitoring stations in Gauteng province, South Africa, including the City of Johannesburg which is on the cusp of being one of the world's megacities and...
Three types of statistical models have been used to create up to 24h forecasts of the zonal and meridional components of wave energy flux levels at three directional buoys located in the Bay of Biscay. Hourly observations of the mean wave period and the significant height covering the 1999–2012 period have been used for this purpose. Additionally, data from the ocean (WAM model) and atmospheric components...
Maintaining situation awareness is a fundamental yet challenging task. In many domains, it's not the lack of data that complicates this task. Instead, the challenge is that relevant information is oftentimes obscured by the shear volume of available data, data that in some cases is incomplete or incorrect. For such domains, it may be difficult to quickly identify and adjudicate relevant information...
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