scholarly journals Multivariate Time Series for Data-Driven Endpoint Prediction in the Basic Oxygen Furnace

2018 ◽  
Author(s):  
Davi Alberto Sala ◽  
Azarakhsh Jalalvand ◽  
Andy Van Yperen-De Deyne ◽  
Erik Mannens
Keyword(s):  
Time Series ◽  
Multivariate Time Series ◽  
Basic Oxygen Furnace ◽  
Data Driven ◽  
Basic Oxygen ◽  
Endpoint Prediction

scholarly journals Partial Correlation-Based Attention for Multivariate Time Series Forecasting

2020 ◽  
Vol 34 (10) ◽  
pp. 13720-13721
Author(s):  
Won Kyung Lee
Keyword(s):  
Time Series ◽  
Partial Correlation ◽  
Time Series Data ◽  
Multivariate Time Series ◽  
Time Series Forecasting ◽  
Data Driven ◽  
Series Data ◽  
Time Lags ◽  
Dependency Structure ◽  
Agnostic Learning

A multivariate time-series forecasting has great potentials in various domains. However, it is challenging to find dependency structure among the time-series variables and appropriate time-lags for each variable, which change dynamically over time. In this study, I suggest partial correlation-based attention mechanism which overcomes the shortcomings of existing pair-wise comparisons-based attention mechanisms. Moreover, I propose data-driven series-wise multi-resolution convolutional layers to represent the input time-series data for domain agnostic learning.

Applying Flame Spectrum on SVC-RVM Modeling for BOF Endpoint Prediction

2013 ◽  
Vol 631-632 ◽  
pp. 870-874
Author(s):  
Yan Ming Shao ◽  
Feng Ji ◽  
Shu An Zhao ◽  
Mu Chun Zhou ◽  
Yan Ru Chen ◽  
...  
Keyword(s):  
Carbon Content ◽  
Relevance Vector Machine ◽  
Basic Oxygen Furnace ◽  
Support Vector ◽  
Contact Method ◽  
Basic Oxygen ◽  
Industrial Data ◽  
End Point ◽  
Endpoint Prediction

A new non-contact method for predicting the basic oxygen furnace(BOF) end point carbon content is proposed in this study. A model applying the flame spectrum of the converter vessel mouth is constructed to carry out the prediction. This model consists two parts, viz. a classifier based on support vector classification to classify the whole period of one BOF heat into two main phases, and a relevance vector machine working at the posterior phase to predict the carbon content. Compared with current non-contact methods of end point carbon content prediction, the proposed method can make better use of the information of the flame of the converter mouth. Simulations on industrial data show that this method yields good results on the classification as well as end point carbon content prediction.

Application of Time Series Analysis for the Prediction of Liquid Metal Height in Basic Oxygen Furnace

2019 ◽  
Author(s):  
Rituparna Biswas ◽  
Sreenivas P S ◽  
Umesh Kumar Singh ◽  
Rishab Singh ◽  
Saroj Kumar Singh ◽  
...  
Keyword(s):  
Time Series ◽  
Liquid Metal ◽  
Time Series Analysis ◽  
Basic Oxygen Furnace ◽  
Basic Oxygen ◽  
Series Analysis
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