Automated Machine Learning Approach Applied to Nuclear Energy Generation Short-Term Forecasting

2021 ◽  
Author(s):  
Jorge Gustavo Sandoval Simão ◽  
Viviana Mariani ◽  
Leandro Coelho
Keyword(s):  
Machine Learning ◽  
Nuclear Energy ◽  
Energy Generation ◽  
Learning Approach ◽  
Short Term ◽  
Machine Learning Approach ◽  
Automated Machine Learning ◽  
Short Term Forecasting

scholarly journals Forecasting cryptocurrency prices time series using machine learning approach

2019 ◽  
Vol 65 ◽  
pp. 02001 ◽  
Author(s):  
Vasily Derbentsev ◽  
Natalia Datsenko ◽  
Olga Stepanenko ◽  
Vitaly Bezkorovainyi
Keyword(s):  
Machine Learning ◽  
Time Series ◽  
Regression Trees ◽  
Learning Approach ◽  
Short Term ◽  
Modified Model ◽  
Machine Learning Approach ◽  
Auto Regressive ◽  
Standard Models ◽  
Short Term Forecasting

This paper describes the construction of the short-term forecasting model of cryptocurrencies’ prices using machine learning approach. The modified model of Binary Auto Regressive Tree (BART) is adapted from the standard models of regression trees and the data of the time series. BART combines the classic algorithm classification and regression trees (C&RT) and autoregressive models ARIMA. Using the BART model, we made a short-term forecast (from 5 to 30 days) for the 3 most capitalized cryptocurrencies: Bitcoin, Ethereum and Ripple. We found that the proposed approach was more accurate than the ARIMA-ARFIMA models in forecasting cryptocurrencies time series both in the periods of slow rising (falling) and in the periods of transition dynamics (change of trend).

Accelerating Surgical Site Infection Abstraction With a Semi-automated Machine-learning Approach

2020 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Steven J. Skube ◽  
Zhen Hu ◽  
Gyorgy J. Simon ◽  
Elizabeth C. Wick ◽  
Elliot G. Arsoniadis ◽  
...  
Keyword(s):  
Machine Learning ◽  
Surgical Site Infection ◽  
Learning Approach ◽  
Site Infection ◽  
Machine Learning Approach ◽  
Automated Machine Learning
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