Szczegóły Szczegóły PDF BIBTEX RIS Tytuł artykułu The Prediction of Moulding Sand Moisture Content Based on the Knowledge Acquired by Data Mining Techniques Tytuł czasopisma Archives of Metallurgy and Materials Rocznik 2016 Numer No 3 September Autorzy Regulski, K. ; Jakubski, J. ; Brzeziński, M. ; Głowacki, M. ; Opaliński, A. Wydział PAN Nauki Techniczne Wydawca Institute of Metallurgy and Materials Science of Polish Academy of Sciences ; Committee of Materials Engineering and Metallurgy of Polish Academy of Sciences Data 2016 Identyfikator DOI: 10.1515/amm-2016-0277 ; e-ISSN 2300-1909 Źródło Archives of Metallurgy and Materials; 2016; No 3 September Referencje Olejarczyk (2012), Parametric representation of TTT diagrams of ADI cast iron of Metallurgy and, Archives Materials, 57, 981, doi.org/10.2478/v10172-012-0065-9 ; Kass (1980), An exploratory technique for investigating large quantities of categorical data, Applied Statistics, 119, doi.org/10.2307/2986296 ; David (2014), The Computer Support of Diagnostics of Circle Crystallizers, Metalurgija, 53, 193. ; Glowacz (2015), Recognition of thermal images of direct current motor with application of area perimeter vector and bayes classifier, Measurement Science Review, 15, 119, doi.org/10.1515/msr-2015-0018 ; Mahesh Parappagoudar (2008), Forward and reverse mappings in green sand mould system using neural networks, Applied Soft Computing, 8, 239, doi.org/10.1016/j.asoc.2007.01.005 ; Sika (2006), Po wdrożeniu programu KonMas - final - jego wykorzystanie do analizy procesu produkcji odlewów na wydziale Odlewni Żeliwa ŚREM XI International Symposium - Modeling of casting and foundry processes, October, 6, 26. ; Speybroeck (2012), Classification and regression trees of, International Journal Public Health, 57, 243, doi.org/10.1007/s00038-011-0315-z ; Jakubski (2010), The usage of data mining tools for green moulding sands quality control of Metallurgy and, Archives Materials, 55, 843. ; Perzyk (2001), Prediction of ductile cast iron quality by artificial neural networks of Material Processing Technology, Journal, 109. ; Warmuzek (2011), A Procedure for in situ Identification of the Intermetallic AITMSi Phase Precipitates in the Microstructure of the Aluminum Alloys Praktische Metallographie - Practical, Metallography, 48, 660, doi.org/10.3139/147.110045 ; Kluska (2011), Rough sets applied to the RoughCast system for steel castings Intelligent Information and Database Systems Part II Third International Conference Korea Proceedings Part II Series : Springer Lecture Notes in Computer Volume in Artificial, Science Lecture Notes Intelligence, 20, 6592, doi.org/10.1007/978-3-642-20042-7_6,Subseries:NgocThanh;-Gun;Janiak(Eds.),1stEdition.580p ; Malinowski (2013), Technological knowledge management system for foundry industry of Metallurgy and, Archives Materials, 58, 965. ; Jakubski (2013), ANN Modelling For The Analysis Of The Green Moulding Sands Properties of Metallurgy and, Archives Materials, 58, 961. ; Perzyk (2005), Modeling of manufacturing processes by learning systems : The naïve Bayesian classifier versus artificial neural networks of Material Processing Technology, Journal, 164. ; Smyksy (2013), Performance evaluation of rotary mixers through monitoring of power energy parameters of Metallurgy and, Archives Materials, 58, 911. ; Opalinski (2013), Scalable web monitoring system in : Computer Science and Information Systems Federated Conference on, IEEE. ; Jakubski (2010), Selected parameters of moulding sands for designing quality control systems of Foundry, Archives Engineering, 10, 11.