Adaptive and robust evidence theory with applications in prediction of floor water inrush in coal mine
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[1] Eric Lefevre,et al. Belief function combination and conflict management , 2002, Inf. Fusion.
[2] Lixin Wu,et al. An Enhanced Localization Method for Moving Targets in Coal Mines Based on Witness Nodes , 2015, Int. J. Distributed Sens. Networks.
[3] Emmanuel Seignez,et al. Real-time driver drowsiness estimation by multi-source information fusion with Dempster–Shafer theory , 2014 .
[4] Shangxian Yin,et al. A study of mine water inrushes by measurements of in situ stress and rock failures , 2015, Natural Hazards.
[5] Liu Hanhu,et al. Technologies of Preventing Coal Mine Water Hazards for Sustainable Development in North China , 2011 .
[6] Ma Jun,et al. A New Dynamic Assessment for Multi-parameters Information of Water Inrush in Coal Mine*☆ , 2012 .
[7] Prem Prakash Jayaraman,et al. City Data Fusion: Sensor Data Fusion in the Internet of Things , 2015, Int. J. Distributed Syst. Technol..
[8] Zaibin Liu,et al. Prediction of Water Inrush Through Coal Floors Based on Data Mining Classification Technique , 2011 .
[9] Catherine K. Murphy. Combining belief functions when evidence conflicts , 2000, Decis. Support Syst..
[10] Yong Deng,et al. Generalized evidence theory , 2014, Applied Intelligence.
[11] Ji-yao An,et al. Combination of Evidence with Different Weighting Factors: A Novel Probabilistic-Based Dissimilarity Measure Approach , 2015, J. Sensors.
[12] Enji Sun,et al. The internet of things (IOT) and cloud computing (CC) based tailings dam monitoring and pre-alarm system in mines , 2012 .
[13] Rolf Haenni,et al. Are alternatives to Dempster's rule of combination real alternatives?: Comments on "About the belief function combination and the conflict management problem" - Lefevre et al , 2002, Inf. Fusion.
[14] Qiang Wu,et al. New development in theory and practice in mine water control in China , 2014, Carbonates and Evaporites.
[15] Yee Leung,et al. An integrated information fusion approach based on the theory of evidence and group decision-making , 2013, Inf. Fusion.
[16] Qi Fan,et al. Fuzzy neural network model applied in the mine water inrush prediction , 2010, International Conference on Image Processing and Pattern Recognition in Industrial Engineering.
[17] Wanfang Zhou,et al. Evaluation of Water Inrush Vulnerability from Aquifers Overlying Coal Seams in the Menkeqing Coal Mine, China , 2015, Mine Water and the Environment.
[18] Lu-wang Chen,et al. Prediction of water-inrush risk areas in process of mining under the unconsolidated and confined aquifer: a case study from the Qidong coal mine in China , 2016, Environmental Earth Sciences.
[19] H. Bai,et al. Groundwater inflow prediction model of karst collapse pillar: a case study for mining-induced groundwater inrush risk , 2015, Natural Hazards.
[20] Peter Friess,et al. Internet of Things Strategic Research Roadmap , 2011 .
[21] Éloi Bossé,et al. Robust combination rules for evidence theory , 2009, Inf. Fusion.
[22] Ming Li,et al. Risk assessment of floor water inrush in coal mines based on secondary fuzzy comprehensive evaluation , 2012 .
[23] Quan Pan,et al. Combination of sources of evidence with different discounting factors based on a new dissimilarity measure , 2011, Decis. Support Syst..
[24] Xiaoli Chu,et al. Energy-Efficient Monitoring in Software Defined Wireless Sensor Networks Using Reinforcement Learning: A Prototype , 2015, Int. J. Distributed Sens. Networks.
[25] Florentin Smarandache,et al. Advances and Applications of DSmT for Information Fusion , 2004 .
[26] Jin Han,et al. Water inrush evaluation of coal seam floor by integrating the water inrush coefficient and the information of water abundance , 2014 .
[27] Youcef Chibani,et al. A DSmT based combination scheme for multi-class classification , 2013, Proceedings of the 16th International Conference on Information Fusion.
[28] Lotfi A. Zadeh,et al. A Simple View of the Dempster-Shafer Theory of Evidence and Its Implication for the Rule of Combination , 1985, AI Mag..
[29] R. Yager. On the dempster-shafer framework and new combination rules , 1987, Inf. Sci..