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Window-Based Feature Engineering for Prediction of Methane Threats in Coal Mines.

, и . RSFDGrC, том 9437 из Lecture Notes in Computer Science, стр. 452-463. Springer, (2015)

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Mining Data from Coal Mines: IJCRS'15 Data Challenge., , , , , , и . RSFDGrC, том 9437 из Lecture Notes in Computer Science, стр. 429-438. Springer, (2015)SQL-Based KDD with Infobright's RDBMS: Attributes, Reducts, Trees., и . RSEISP, том 8537 из Lecture Notes in Computer Science, стр. 28-41. Springer, (2014)A Metadata Diagnostic Framework for a New Approximate Query Engine Working with Granulated Data Summaries., , и . IJCRS (1), том 10313 из Lecture Notes in Computer Science, стр. 623-643. Springer, (2017)Reducts in Rough Sets: Algorithmic Insights, Open Source Libraries and Applications (Tutorial - Extended Abstract)., и . FedCSIS, том 35 из Annals of Computer Science and Information Systems, стр. 71. (2023)Window-Based Feature Engineering for Prediction of Methane Threats in Coal Mines., и . RSFDGrC, том 9437 из Lecture Notes in Computer Science, стр. 452-463. Springer, (2015)A framework for learning and embedding multi-sensor forecasting models into a decision support system: A case study of methane concentration in coal mines., , , , , , , и . Inf. Sci., (2018)Knowledge Pit - A Data Challenge Platform., , , и . CS&P, том 1492 из CEUR Workshop Proceedings, стр. 191-195. CEUR-WS.org, (2015)Reinventing Infobright's Concept of Rough Calculations on Granulated Tables for the Purpose of Accelerating Modern Data Processing Frameworks., , и . IEEE BigData, стр. 5405-5412. IEEE, (2020)Toward Interactive Attribute Selection with Infolattices - A Position Paper., , , и . IJCRS (2), том 10314 из Lecture Notes in Computer Science, стр. 526-539. Springer, (2017)SQL-Based Heuristics for Selected KDD Tasks over Large Data Sets., и . FedCSIS, стр. 303-310. (2012)