Krzysztof Regulski

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

D. Wilk-Kołodziejczyk, Krzysztof Regulski, G. Gumienny · The International Journal of Advanced Manufacturing Technology · 2016 · 58 citations · Full text

Materials Science, Engineering, Machine Learning +13

Data mining tools in identifying the components of the microstructure of compacted graphite iron based on the content of alloying elements

D. Wilk-Kołodziejczyk, Krzysztof Regulski, G. Gumienny et al. · The International Journal of Advanced Manufacturing Technology · 2017 · 21 citations · Full text

Engineering, Industrial Engineering, Mechanical Engineering +22

Diagnosis of casting defects using uncertain and incomplete knowledge

Z. Górny, S. Kluska-Nawarecka, D. Wilk-Kołodziejczyk et al. · Archives of Metallurgy and Materials · 2010 · 20 citations · Full text

Reliability, Reliability Engineering, Engineering +7

Methodology for the Construction of a Rule-Based Knowledge Base Enabling the Selection of Appropriate Bronze Heat Treatment Parameters Using Rough Sets

Z. Górny, S. Kluska-Nawarecka, D. Wilk-Kołodziejczyk et al. · Archives of Metallurgy and Materials · 2015 · 17 citations · Full text

Knowledge Base, Engineering, Rough Set Theory +13

Application of Selected Artificial Intelligence Methods in a System Predicting the Microstructure of Compacted Graphite Iron

B. Mrzygłód, G. Gumienny, D. Wilk-Kołodziejczyk et al. · Journal of Materials Engineering and Performance · 2019 · 16 citations · Full text

Artificial Intelligence, Engineering, Industrial Engineering +19