Details

Title

Approximation of Ausferrite Content in the Compacted Graphite Iron with the Use of Combined Techniques of Data Mining

Journal title

Archives of Foundry Engineering

Yearbook

2017

Volume

vol. 17

Issue

No 3

Authors

Keywords

Application of information technologies in the field of foundry ; Compacted graphite iron ; Ausferrite ; Data Mining ; Regression

Divisions of PAS

Nauki Techniczne

Publisher

The Katowice Branch of the Polish Academy of Sciences

Date

2017

Type

Artykuły / Articles

Identifier

DOI: 10.1515/afe-2017-0102 ; eISSN 2299-2944

Source

Archives of Foundry Engineering; 2017; vol. 17; No 3

References

Guzik (2009), study on the structure and mechanical properties of compacted cast iron with pearlitic - ferritic matrix of Foundry, Archives Engineering, 9, 55. ; David (2013), s Desks Surface Diagnostics with Usage of Robotic System of and, Archives Metallurgy Materials, 30, 907. ; De Andrés (2011), de Cos Bankruptcy forecasting : a hybrid approach using fuzzy c - means clustering and multivariate adaptive regression splines with, Expert Systems Applications, 12, 1866. ; Kluska (2007), The logic of plausible reasoning in the diagnosis of castings defects of and, Archives Metallurgy Materials, 26, 375. ; Shaikhina (2017), Decision tree and random forest models for outcome prediction in antibody incompatible kidney transplantation Biomed Control http dx doi org, Signal Process, 19, doi.org/10.1016/j.bspc.2017.01.012 ; Plonsky (2016), Multiple Regression as a flexible alternative to ANOVA in Research in Second, Studies Language Acquisition, 13, 1, doi.org/10.1017/S0272263116000231 ; Smyksy (2013), Performance evaluation of rotary mixers through monitoring of power energy parameters of and, Archives Metallurgy Materials, 31, 911. ; Pytel (2014), Evaluation of selected properties in austempered compacted cast iron Transactions of Foundry Research Institute, null, 23, doi.org/10.7356/iod.2014.18 ; Breiman (1999), Random forest http dx org, Learn, 20, 1, doi.org/10.1023/A:1010933404324 ; David (2016), Heuristic modeling of casting processes under the conditions uncertainty of Civil and Mechanical, Archives Engineering, 29, 179. ; Pietrowski (2000), of knowledge about compacted cast iron Solidification of Metals and Alloys in Polish, Compendium, 279. ; Soiński (2014), Initial Assessment of Abrasive Wear Resistance of Austempered Cast Iron with Compacted Graphite of and, Archives Metallurgy Materials, 59, doi.org/10.2478/amm-2014-0183 ; Yang (2007), Studies of stability and robustness for artificial neural networks and boosted decision trees, Meth, 22, 574. ; Jakubski (2013), St Modelling for the analysis of the Green Moulding properties of and, ANN Archives Metallurgy Materials, 16, 961. ; Malash (2010), Piecewise Linear Regression Statistical Method for the Analysis of Experimental Adsorption Data by the Intraparticle - Diffusion Models http dx org, Chemical Engineering Journal, 163. ; Kluska (2014), - assisted integration of knowledge in the context of identification of the causes of defects in castings of Metallurgy and, Computer Archives Materials, 23, 59. ; Mrzygłód (null), Effect of heat treatment parameters on the formation of ADI microstructure with additions of Ni Cu Mo of and, Archives Metallurgy Materials, 24, 2015. ; Mukhopadhyay (2009), Prediction of mechanical property of steel strips using multivariate adaptive regression splines, Stat, 15. ; Warmuzek (2011), procedure of in situ identification of the intermetallic AlTMSi phase precipitates in the microstructure of the aluminum alloys Practical, Metallography, 27, 12. ; Abraham (2001), Rainfall forecasting using soft computing models and multivariate adaptive regression splines Transactions Special issue on Fusion of in Industrial Applications, IEEE Soft Computing Computing, 1. ; Kluska (2011), Rough sets applied to the RoughCast system for steel castings Intelligent and Systems Part II Springer in, Information Database Lecture Notes Computer Science, 28, 6592. ; Rauch (2013), system for identification of material models on the basis of plastometric tests of Metallurgy and Materials amm, Computer Archives, 18, 737. ; Friedman (2003), Recent advances in predictive machine learning of University, Proceedings Stanford, 21. ; Skvarenina (2006), Laser - assisted machining of compacted graphite iron of Machine Tools and Manufacture, International Journal, 46, 1. ; Behera (2013), Tool path compensation strategies for single point incremental sheet forming using multivariate adaptive regression splines -, Computer Aided Design, 14. ; Regulski (2016), Comparative analysis of the properties of the Nodular Cast Iron with Carbides and the Austempered Ductile Iron with use of the machine learning and the Support Vector Machine The, International Journal of Advanced Manufacturing Technology, 87. ; Olejarczyk (2014), Mathematical model of the process of pearlite austenitization of and, Archives Metallurgy Materials, 25, 59. ; Sztangret (2012), Application of inverse analysis with metamodelling for identification of metal flow stress, Canadian Metallurgical Quarterly, 17, 440. ; Glowacz (2017), Recognition of rotor damages in a DC motor using acoustic signals, Bulletin of the Polish Academy of Sciences Technical Sciences, 187. ; Maciol (2007), Arrangement of flow modification devices in continuous casting tundish based on multicriterion optimization of and, Archives Metallurgy Materials, 1.
×