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All issues Volume 342 (2021) MATEC Web Conf., 342 (2021) 05006 References
Open Access
Issue
MATEC Web Conf.
Volume 342, 2021
9th edition of the International Multidisciplinary Symposium “UNIVERSITARIA SIMPRO 2021”: Quality and Innovation in Education, Research and Industry – the Success Triangle for a Sustainable Economic, Social and Environmental Development”
Article Number 05006
Number of page(s) 11
Section Developments in Systems Control, Information Technology and Cybersecurity
DOI https://doi.org/10.1051/matecconf/202134205006
Published online 20 July 2021
  1. G. Castellano, A.M. Fanelli, C. Mencar, Generation of interpretable fuzzy granules by a double-clustering technique. Archives of Control Sciences: Special issue on Granular Computing 12 (4), 397-410 (2002) [Google Scholar]
  2. E. Czogala, J. Leski, Fuzzy and neuro-fuzzy intelligent systems, Physica-Verlag (2000) [Google Scholar]
  3. M. Galetakis, A. Vasiliou, Applications of fuzzy inference systems in mineral industryoverview. Book chapter in Expert System Software, editors: J. M. Segura and A. C. Reiter, 211-217 (2010) [Google Scholar]
  4. M. Galetakis, T. Michalakopoulos, A. Bajcar, C. Roumpos, M. Lazar, P. Svoboda, Project BEWEXMIN: Bucket wheel excavators operating Under difficult mining conditions including unmineable Inclusions and geological structures with excessive mining resistance, Proceedings of 13th International Symposium Continuous Surface Mining, ISCSM 2016, 103-114 (2016) [Google Scholar]
  5. M. Galetakis, A. Vafidis, A. Vasiliou, G. Kritikakis, V. Deligiorgis, T. Michalakopoulos, G. Apostolopoulos, C. Roumpos, F. Pavloudakis, Development of a fuzzy inference system for avoiding collision of bucket wheel excavator equipped with electromagnetic (EM) sensors with hard rock inclusions, Górnictwo Odkrywkowe, 59 4, 16-22 (2018) [Google Scholar]
  6. L. Guo, Y. Qi, Y. Wang, F. Yang, Fuzzy comprehensive evaluation on relationship of coal maceral and porosity, International Symposium on Safety Science and Technology, Procedia Engineering 45, 962-966 (2012) [Google Scholar]
  7. M. Hadizadeh, A. Farganegan, M. Noaparast, Supervisory Fuzzy Expert Controller for Sag Mill Grinding Circuits: Sungun Copper Concentrator, Mineral Processing and Extractive Metallurgy Review, 38:3, 168-179 (2017) [Google Scholar]
  8. S. Hoogendoorn, S. Hoogendoorn-Lanser, H. Schuurman, Fuzzy perspectives in traffic engineering, Workshop on Intelligent Traffic Management Models, (1999) [Google Scholar]
  9. I.M. Jiskani, Q. Cai, W. Zhou, X. Lu, Assessment of risks impeding sustainable mining in Pakistan using fuzzy synthetic evaluation, Resources Policy 69, 1-13 (2020) [Google Scholar]
  10. Y. Kim, K. Choe, R. Ri, Application of fuzzy logic and geometric average: A Cu sulfide deposits potential mapping case study from Kapsan Basin, DPR Korea, Ore Geology Reviews 107, 239-247 (2019) [Google Scholar]
  11. Mathworks Inc, Fuzzy Logic Toolbox for use with Matlab, User’s Guide version 2 (1999) [Google Scholar]
  12. J. Meech, The evolution of intelligent systems in the mining industry, In Proceedings of the international conference on mineral process modeling, simulation and control, 1–30 (2006) [Google Scholar]
  13. A. Mottahedi, M. Ataei, Fuzzy fault tree analysis for coal burst occurrence probability in underground coal mining. Tunnelling and Underground Space Technology 83, 165-174 (2019) [Google Scholar]
  14. L. Overmeyer, M. Kesting, K. Jansen, SIMT Technology – Sensory identification of material type and detection of the interfaces, Bulk Solids Handling, 27 (2), 112118 (2007) [Google Scholar]
  15. P. Pahlavani, S. Riahi, B. Bidgeli, Ranking potentially favorable mineralization zones using fuzzy VIKOR vs. Dempster-Shafer-fuzzy AHP methods, a case study: southeast of the Sarcheshmeh copper mine, Kerman, Iran. Arabian journal of Geosciences 13:1167, 1-21 (2020) [Google Scholar]
  16. M. Parsa, A. Maghsoudi, M. Yousefi, An improved data-driven fuzzy mineral prospectivity mapping procedure; cosine amplitude-based similarity approach to delineate exploration targets, International Journal of Applied Earth Observation and Geoinformation 58, 157-167 (2017) [Google Scholar]
  17. M. Piltan, E. Mehmanchi, S.F. Ghaderi, Proposing a decision-making model using analytical hierarchy process and fuzzy expert system for prioritizing industries in installation of combined heat and power systems, Expert Systems with Applications 39, 1124-1133 (2012) [Google Scholar]
  18. R. Qi, S. Li, L. Qu, L. Sun, C. Gong, Critical factors to green mining construction in China: A two-step fuzzy DEMATEL analysis of state-owned coal mining enterprises, Journal of Cleaner Production 273, 1-14 (2020) [Google Scholar]
  19. T.M. Sayers, M.G.H. Bell, T. Mieden, F. Busch, Improving the traffic responsiveness of signal controllers using fuzzy logic, IEE Colloquium on Urban Congestion Management 207, 6/1-6/4 (1995) [Google Scholar]
  20. T.M. Sayers, M.G.H. Bell, T. Mieden, F. Busch, Traffic responsive signal control using fuzzy logic—a practical modular approach, Proceedings of the 1996 IEE Colloquium on Fuzzy Logic Controllers In Practice 200, 5/1-5/4 (1996) [Google Scholar]
  21. F. Sitorus, P.R. Brito-Parada, Equipment selection in mineral processing A sensitivity analysis approach for a fuzzy multiple criteria decision making model, Minerals Engineering 150, 1-8 (2020) [Google Scholar]
  22. K.A. Tripathi, Review on Knowledge-based Expert System: Concept and Architecture, IJCA Special Issue on “Artificial Intelligence Techniques Novel Approaches & Practical Applications”, 19-23 (2011) [Google Scholar]
  23. D. P. Tripathi, C.K. Ala, Risk Assessment in Underground Coalmines Using Fuzzy Logic in the Presence of Uncertainty, Journal of The Institution of Engineers (India): Series D, 99, 157–163 (2018) [Google Scholar]
  24. A. Vafidis, N. Economou, M. Galetakis, A. Vasiliou, T. Michalakopoulos, G. Apostolopoulos, Assessing the potential of ground penetrating radar (GPR) to detect hard geological formations and inclusions during the excavation by bucket--wheel excavators, Proceedings of 13th International Symposium Continuous Surface Mining, ISCSM 2016, 631-643 (2016) [Google Scholar]
  25. F. Van Zyl, F. Paquot, F. Metzner, Fouche, A. Gomez, Implementation of a SAG Grinding Expert System at Kansanshi Mine – Zambia, 16th IFAC Symposium on Automation in Mining, Mineral and Metal Processing 46, Issue 16, 176-181 (2013) [Google Scholar]
  26. F. Wu, T. Chai, Soft sensing method for magnetic tube recovery ratio via fuzzy systems and neural networks. Neurocomputing 73, 2489-2497 (2010) [Google Scholar]
  27. Z. Yan, X. Wang, Y. Fu, Study on Early warning model of Coal mining engineering with Fuzzy AHP, Systems Engineering Procedia 5, 113-118 (2012) [Google Scholar]
  28. L.A. Zadeh, Toward a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic, Fuzzy Sets and Systems 90, 111–117 (1997) [Google Scholar]

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