His primary areas of study are Blast furnace, Genetic algorithm, Artificial neural network, Multi-objective optimization and Mathematical optimization. His Blast furnace study combines topics in areas such as Data mining, Waste management, Steel mill and Process engineering. His studies examine the connections between Waste management and genetics, as well as such issues in Steelmaking, with regards to Carbon dioxide.
Henrik Saxén has researched Genetic algorithm in several fields, including Evolutionary computation, Pareto principle, Biological system and Evolutionary algorithm. Henrik Saxén is interested in Feedforward neural network, which is a field of Artificial neural network. His Mathematical optimization research is multidisciplinary, incorporating elements of Simulation and Relevance.
Henrik Saxén mainly focuses on Blast furnace, Artificial neural network, Metallurgy, Coke and Hearth. His Blast furnace research incorporates themes from Discrete element method, Mechanics, Waste management, Slag and Mineralogy. His work is dedicated to discovering how Waste management, Steelmaking are connected with Steel mill and other disciplines.
His work deals with themes such as Genetic algorithm, Mathematical optimization and Data mining, which intersect with Artificial neural network. His studies in Coke integrate themes in fields like Nuclear engineering and Basic oxygen steelmaking. His Feedforward neural network research includes themes of Time delay neural network and Nonlinear system.
Henrik Saxén spends much of his time researching Blast furnace, Metallurgy, Hearth, Discrete element method and Slag. His Blast furnace research includes elements of Nuclear engineering, Coke and Image, Computer vision, Artificial intelligence. In general Metallurgy, his work in Chromium, Microstructure and Leaching is often linked to Off line linking many areas of study.
His research investigates the connection between Hearth and topics such as Mining engineering that intersect with problems in Principal component analysis. The Discrete element method study combines topics in areas such as Porosity, Pellet, Mass fraction, Flow and Angle of repose. His Slag study integrates concerns from other disciplines, such as Carbon capture and storage, Carbonation and Steelmaking.
Henrik Saxén mainly investigates Metallurgy, Chromium, Blast furnace, Angle of repose and Discrete element method. His Chromium research integrates issues from Slag, Spinel and Decomposition. Henrik Saxén integrates Blast furnace and Off line in his research.
Henrik Saxén interconnects Conical surface, Pile and Rolling resistance in the investigation of issues within Angle of repose. He combines subjects such as Mechanics and Shear modulus with his study of Rolling resistance. The study incorporates disciplines such as Pollutant, Ammonium, Steelmaking, Magnesium and Anhydrous in addition to Leaching.
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A genetic algorithms based multi-objective neural net applied to noisy blast furnace data
F. Pettersson;N. Chakraborti;H. Saxén.
soft computing (2007)
Nonlinear Prediction of the Hot Metal Silicon Content in the Blast Furnace
Henrik Saxén;Frank Pettersson.
Isij International (2007)
Experimental and DEM study of segregation of ternary size particles in a blast furnace top bunker model
Yaowei Yu;Henrik Saxén.
Chemical Engineering Science (2010)
Data-Driven Time Discrete Models for Dynamic Prediction of the Hot Metal Silicon Content in the Blast Furnace—A Review
Henrik Saxen;Chuanhou Gao;Zhiwei Gao.
IEEE Transactions on Industrial Informatics (2013)
Model of the state of the blast furnace hearth
Jan Torrkulla;Henrik Saxén.
Isij International (2000)
Discrete element method simulation of properties of a 3D conical hopper with mono-sized spheres
Yaowei Yu;Henrik Saxén.
Advanced Powder Technology (2011)
Analyzing Leaching Data for Low-Grade Manganese Ore Using Neural Nets and Multiobjective Genetic Algorithms
Frank Pettersson;Arijit Biswas;Prodip Kumar Sen;Henrik Saxén.
Materials and Manufacturing Processes (2009)
Cu―Zn separation by supported liquid membrane analyzed through Multi-objective Genetic Algorithms
Debanga Nandan Mondal;Kadambini Sarangi;Frank Pettersson;Prodip Kumar Sen.
Genetic Programming Evolved through Bi-Objective Genetic Algorithms Applied to a Blast Furnace
Brijesh Kumar Giri;Frank Pettersson;Henrik Saxén;Nirupam Chakraborti.
Materials and Manufacturing Processes (2013)
Evolving Nonlinear Time-Series Models of the Hot Metal Silicon Content in the Blast Furnace
Henrik Saxén;Frank Pettersson;Kiran Gunturu.
Materials and Manufacturing Processes (2007)
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