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Deep learning has achieved significant improvement in various machine learning tasks including image recognition, speech recognition, machine translation and etc. Inspired by the huge success of the paradigm, there have been lots of tries to apply deep learning algorithms to data analytics problems with big data including traffic flow prediction. However, there has been no attempt to apply the deep...
The primary goal of the model proposed in this paper is to predict airline delays caused by inclement weather conditions using data mining and supervised machine learning algorithms. US domestic flight data and the weather data from 2005 to 2015 were extracted and used to train the model. To overcome the effects of imbalanced training data, sampling techniques are applied. Decision trees, random forest,...
This paper presents an auto-delay offset cancellation technique for time difference repeating amplifier. Pipeline time-to-digital converter (TDC) achieves fine resolution by amplifying the time residue. Therefore the linearity of the time difference amplifier (TA) is important in pipeline TDC. The pulse-train TA, time difference repeating amplifier, was proposed to improve this recently. However,...
Utility communications are increasingly required to support machine-to-machine (M2M) communications for hundreds to millions of end devices ranging from meters and PMUs to tiny sensors, high-powered sensors (e.g., intelligent electric devices), and electric vehicles. The Software Defined Network (SDN) concept provides inherent features to support in a self-configurable and scalable manner the deployment...
Aligned with significant attention to smart grid, timely and precise analysis of grid data that is continuously reported from a massive number of field devices such as sensors, meters, and so on, is considered a key factor to accelerate smart grid deployment. However, many utilities today have no grid data analytic system, or have grid data analytic systems that are operated in an off-line manner...
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