Application of a genetic algorithm based model selection algorithm for identification of carbide-based hot metal desulfurization

2020 ◽  
Vol 92 ◽  
pp. 106330
Author(s):  
Tero Vuolio ◽  
Ville-Valtteri Visuri ◽  
Aki Sorsa ◽  
Seppo Ollila ◽  
Timo Fabritius
Keyword(s):  
Genetic Algorithm ◽  
Model Selection ◽  
Selection Algorithm ◽  
Hot Metal ◽  
Hot Metal Desulfurization

scholarly journals Genetic Algorithm‐Based Variable Selection in Prediction of Hot Metal Desulfurization Kinetics

2019 ◽  
Vol 90 (8) ◽  
pp. 1900090 ◽  
Author(s):  
Tero Vuolio ◽  
Ville‐Valtteri Visuri ◽  
Aki Sorsa ◽  
Timo Paananen ◽  
Timo Fabritius
Keyword(s):  
Genetic Algorithm ◽  
Variable Selection ◽  
Hot Metal ◽  
Hot Metal Desulfurization

scholarly journals Accounting for cell lineage and sex effects in the identification of cell-specific DNA methylation using a Bayesian model selection algorithm

PLoS ONE ◽  
2017 ◽  
Vol 12 (9) ◽  
pp. e0182455 ◽  
Author(s):  
Nicole White ◽  
Miles Benton ◽  
Daniel Kennedy ◽  
Andrew Fox ◽  
Lyn Griffiths ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Model Selection ◽  
Bayesian Model ◽  
Cell Lineage ◽  
Bayesian Model Selection ◽  
Selection Algorithm ◽  
Sex Effects

scholarly journals Hot Metal Desulfurization Behavior with Dolomite Flux

2013 ◽  
Vol 53 (6) ◽  
pp. 1020-1027 ◽  
Author(s):  
Yoshie Nakai ◽  
Naoki Kikuchi ◽  
Yuji Miki ◽  
Yasuo Kishimoto ◽  
Tomoo Isawa ◽  
...  
Keyword(s):  
Hot Metal ◽  
Hot Metal Desulfurization

scholarly journals Powder Blasting in Hot Metal Desulfurization by Mechanical Stirring Process

2017 ◽  
Vol 57 (6) ◽  
pp. 1029-1036 ◽  
Author(s):  
Yoshie Nakai ◽  
Ikuhiro Sumi ◽  
Naoki Kikuchi ◽  
Kotaro Tanaka ◽  
Yuji Miki
Keyword(s):  
Hot Metal ◽  
Mechanical Stirring ◽  
Powder Blasting ◽  
Hot Metal Desulfurization

scholarly journals Hot metal desulfurization by marble waste and fluorspar

2012 ◽  
Vol 65 (2) ◽  
pp. 233-240 ◽  
Author(s):  
Felipe Nylo de Aguiar ◽  
Felipe Fardin Grillo ◽  
Jorge Alberto Soares Tenório ◽  
José Roberto de Oliveira
Keyword(s):  
Chemical Composition ◽  
Chemical Analysis ◽  
Pig Iron ◽  
Hot Metal ◽  
Industrial Mixture ◽  
Desulfurization Process ◽  
Hot Metal Desulfurization ◽  
Vacuum Sampling ◽  
Marble Waste

The objective of this paper is to present an analysis of the use of residual marble mixtures in the pig iron desulfurization process. The study involved the use of: marble waste, fluorspar, lime, and hot metal. Four mixtures were made and added to a liquid hot metal - with known chemical composition - at a temperature of 1450ºC. The mass of each element was calculated from its chemical analysis and compared with an industrial mixture. All of the four mixtures used in the experiments were stirred by a mechanical stirrer. Samples were collected by vacuum sampling for times of 5, 10, 15, 20, and 30 minutes, and analysis was performed to check sulfur variation in the bath with time. The results were analyzed and they verified that it was possible to use marble waste as a desulfurizer.

scholarly journals Influence of Solid CaO and Liquid Slag on Hot Metal Desulfurization

2012 ◽  
Vol 52 (1) ◽  
pp. 10-17 ◽  
Author(s):  
Koichi Takahashi ◽  
Keita Utagawa ◽  
Hiroyuki Shibata ◽  
Shin-ya Kitamura ◽  
Naoki Kikuchi ◽  
...  
Keyword(s):  
Liquid Slag ◽  
Hot Metal ◽  
Hot Metal Desulfurization

scholarly journals Non-linear contour-based multidirectional intra coding

2018 ◽  
Vol 7 ◽  
Author(s):  
Thorsten Laude ◽  
Jan Tumbrägel ◽  
Marco Munderloh ◽  
Jörn Ostermann
Keyword(s):  
Model Selection ◽  
Image Coding ◽  
Reference Area ◽  
Selection Algorithm ◽  
Still Image ◽  
Intra Coding ◽  
Coding Efficiency ◽  
Contour Model ◽  
Non Linear ◽  
Contour Models

AbstractIntra coding is an essential part of all video coding algorithms and applications. Additionally, intra coding algorithms are predestined for an efficient still image coding. To overcome limitations in existing intra coding algorithms (such as linear directional extrapolation, only one direction per block, small reference area), we propose non-linear Contour-based Multidirectional Intra Coding. This coding mode is based on four different non-linear contour models, on the connection of intersecting contours and on a boundary recall-based contour model selection algorithm. The different contour models address robustness against outliers for the detected contours and evasive curvature changes. Additionally, the information for the prediction is derived from already reconstructed pixels in neighboring blocks. The achieved coding efficiency is superior to those of related works from the literature. Compared with the closest related work, BD rate gains of 2.16% are achieved on average.

Air quality management using genetic algorithm based heuristic fuzzy time series model

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Lalit Bhagat ◽  
Gunjan Goyal ◽  
Dinesh C.S. Bisht ◽  
Mangey Ram ◽  
Yigit Kazancoglu
Keyword(s):  
Genetic Algorithm ◽  
Air Pollution ◽  
Time Series ◽  
Air Quality ◽  
Quality Management ◽  
Fuzzy Time Series ◽  
Selection Algorithm ◽  
Content Type ◽  
Proposed Model ◽  
Adaptive Time

PurposeThe purpose of this paper is to provide a better method for quality management to maintain an essential level of quality in different fields like product quality, service quality, air quality, etc.Design/methodology/approachIn this paper, a hybrid adaptive time-variant fuzzy time series (FTS) model with genetic algorithm (GA) has been applied to predict the air pollution index. Fuzzification of data is optimized by GAs. Heuristic value selection algorithm is used for selecting the window size. Two algorithms are proposed for forecasting. First algorithm is used in training phase to compute forecasted values according to the heuristic value selection algorithm. Thus, obtained sequence of heuristics is used for second algorithm in which forecasted values are selected with the help of defined rules.FindingsThe proposed model is able to predict AQI more accurately when an appropriate heuristic value is chosen for the FTS model. It is tested and evaluated on real time air pollution data of two popular tourism cities of India. In the experimental results, it is observed that the proposed model performs better than the existing models.Practical implicationsThe management and prediction of air quality have become essential in our day-to-day life because air quality affects not only the health of human beings but also the health of monuments. This research predicts the air quality index (AQI) of a place.Originality/valueThe proposed method is an improved version of the adaptive time-variant FTS model. Further, a nature-inspired algorithm has been integrated for the selection and optimization of fuzzy intervals.

Sign in / Sign up

Export Citation Format

Share Document