Editorial: Deep Learning for Big Data Analytics
نویسندگان
چکیده
منابع مشابه
P-V-L Deep: A Big Data Analytics Solution for Now-casting in Monetary Policy
The development of new technologies has confronted the entire domain of science and industry with issues of big data's scalability as well as its integration with the purpose of forecasting analytics in its life cycle. In predictive analytics, the forecast of near-future and recent past - or in other words, the now-casting - is the continuous study of real-time events and constantly updated whe...
متن کاملA Fuzzy TOPSIS Approach for Big Data Analytics Platform Selection
Big data sizes are constantly increasing. Big data analytics is where advanced analytic techniques are applied on big data sets. Analytics based on large data samples reveals and leverages business change. The popularity of big data analytics platforms, which are often available as open-source, has not remained unnoticed by big companies. Google uses MapReduce for PageRank and inverted indexes....
متن کاملGuest Editorial: Big Data Analytics and the Web
THE paper by Shao et al., “Clustering Big SpatiotemporalInterval Data,” focuses on clustering big spatiotemporal data, which are common in the emerging Web of Things (WoT), where a large number of sensors are deployed for continuously collecting data. The authors explore a novel way to cluster massive Web data with spatiotemporal intervals in multiple Euclidean spaces, as well as a new energy f...
متن کاملCognitive Analytics: Going Beyond Big Data Analytics and Machine Learning
This chapter defines analytics and traces its evolution from its origin in 1988 to its current stage—cognitive analytics. We discuss types of learning and describe classes of machine learning algorithms. Given this backdrop, we propose a reference architecture for cognitive analytics and indicate ways to implement the architecture. A few cognitive analytics applications are briefly described. T...
متن کاملApplication of Big Data Analytics in Power Distribution Network
Smart grid enhances optimization in generation, distribution and consumption of the electricity by integrating information and communication technologies into the grid. Today, utilities are moving towards smart grid applications, most common one being deployment of smart meters in advanced metering infrastructure, and the first technical challenge they face is the huge volume of data generated ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Mobile Networks and Applications
سال: 2021
ISSN: ['1383-469X', '1572-8153']
DOI: https://doi.org/10.1007/s11036-021-01851-0