Smart city driven by Big Data and Internet of Things(loT)has become a most promising trend of the *** one important function of smart city,event alert based on time series prediction is faced with the challenge of how...
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Smart city driven by Big Data and Internet of Things(loT)has become a most promising trend of the *** one important function of smart city,event alert based on time series prediction is faced with the challenge of how to extract and represent discriminative features of sensing knowledge from the massive sequential data generated by iot *** this paper,a framework based on sparse representa-tion model(SRM)for time series prediction is proposed as an efficient approach to tackle this *** dividing the over-complete dictionary into upper and lower parts,the main idea of SRM is to obtain the sparse representation of time series based on the upper part firstly,and then realize the prediction of future values based on the lower *** choice of different dictionaries has a significant impact on the performance of *** paper focuses on the study of dictionary construction strategy and summarizes eight variants of *** results demonstrate that SRM can deal with different types of time series prediction flexibly and effectively.
Bike-sharing is becoming popular in the world, providing a convenient service for citizens. The system has to redistribute bikes among different stations frequently to solve the imbalance of spatial distribution. Real...
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With the rapid development of mobile payment technology in China, people can use smartphone with some mobile payment apps (such as Alipay, WeChat pay and Apple pay etc.) to pay bills instead of paying cash. Some comme...
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This paper proposes a kind of supervised cascaded denoising convolutional auto-encoders (CDCAE), aiming to accurately recover the missing load data in electric power system. The one-dimensional load data are reshaped ...
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ISBN:
(数字)9781728197241
ISBN:
(纸本)9781728197258
This paper proposes a kind of supervised cascaded denoising convolutional auto-encoders (CDCAE), aiming to accurately recover the missing load data in electric power system. The one-dimensional load data are reshaped as two-dimensional image for data enhancement, which enables the convolutional neural network (CNN) to understand the semantics of load data. Numerical results in comparison with similar day filling (SDF) clearly validate the effectiveness of the proposed CDCAE in accuracy.
As user-generated reviews from Location Based Social Networks (LBSNs) are becoming increasingly pervasive, exploiting sentiment analysis based on user’s textual reviews for location recommendation has become a popula...
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The absorption coefficient spectra and refractive index spectra of food grade, industrial grade and pharmaceutical grade paraffin wax, the three different types of paraffin wax within the terahertz frequency range fro...
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