Using GIS, GPS, GPRS and RFID, a dynamic information management system of digital mining in an open pit was designed and developed.A linear programming model was set up in a practical application.By the model, the sys...Using GIS, GPS, GPRS and RFID, a dynamic information management system of digital mining in an open pit was designed and developed.A linear programming model was set up in a practical application.By the model, the system can automatically draw up production plan of ore blending well every day.The system can monitor and dispatch open-pit trucks and shovels well, and can play back their historical paths.It can monitor and control the process of mining production in real time.By RFID, the system can also count the number of trucks'delivery and shovels'loading automatically.Experiments on real scenes show that the performance of this system is stable and can satisfy production standards of mining in open pits.展开更多
An optimization model of underground mining method selection was established on the basis of the unascertained measurement theory.Considering the geologic conditions,technology,economy and safety production,ten main f...An optimization model of underground mining method selection was established on the basis of the unascertained measurement theory.Considering the geologic conditions,technology,economy and safety production,ten main factors influencing the selection of mining method were taken into account,and the comprehensive evaluation index system of mining method selection was constructed.The unascertained evaluation indices corresponding to the selected factors for the actual situation were solved both qualitatively and quantitatively.New measurement standards were constructed.Then,the unascertained measurement function of each evaluation index was established.The index weights of the factors were calculated by entropy theory,and credible degree recognition criteria were established according to the unascertained measurement theory.The results of mining method evaluation were obtained using the credible degree criteria,thus the best underground mining method was determined.Furthermore,this model was employed for the comprehensive evaluation and selection of the chosen standard mining methods in Xinli Gold Mine in Sanshandao of China.The results show that the relative superiority degrees of mining methods can be calculated using the unascertained measurement optimization model,so the optimal method can be easily determined.Meanwhile,the proposed method can take into account large amount of uncertain information in mining method selection,which can provide an effective way for selecting the optimal underground mining method.展开更多
To detect the DoS in networks by applying association rules mining techniques, we propose that association rules and frequent itemsets can be employed to find DoS pattern in packet streams which describe traffic and u...To detect the DoS in networks by applying association rules mining techniques, we propose that association rules and frequent itemsets can be employed to find DoS pattern in packet streams which describe traffic and user behaviors. The method extracts information from the log analysis of submitted packets using the algorithm which depends on the definition of the intrusion. Large itemsets were extracted to represent the super facts to build the association analysis for the intrusion. Network data files were analysed for experiments. The analysis and experimental results are encouraging with better performance as packet frequency number increases.展开更多
基金Supported by Shannxi Leading Academic Discipline ProjectShannxi Science and Technology Project(the Key Industries R&D Programme)(2009K08-25)
文摘Using GIS, GPS, GPRS and RFID, a dynamic information management system of digital mining in an open pit was designed and developed.A linear programming model was set up in a practical application.By the model, the system can automatically draw up production plan of ore blending well every day.The system can monitor and dispatch open-pit trucks and shovels well, and can play back their historical paths.It can monitor and control the process of mining production in real time.By RFID, the system can also count the number of trucks'delivery and shovels'loading automatically.Experiments on real scenes show that the performance of this system is stable and can satisfy production standards of mining in open pits.
基金Project(2007CB209402) supported by the National Basic Research Program of China Project(SKLGDUEK0906) supported by the Research Fund of State Key Laboratory for Geomechanics and Deep Underground Engineering of China
文摘An optimization model of underground mining method selection was established on the basis of the unascertained measurement theory.Considering the geologic conditions,technology,economy and safety production,ten main factors influencing the selection of mining method were taken into account,and the comprehensive evaluation index system of mining method selection was constructed.The unascertained evaluation indices corresponding to the selected factors for the actual situation were solved both qualitatively and quantitatively.New measurement standards were constructed.Then,the unascertained measurement function of each evaluation index was established.The index weights of the factors were calculated by entropy theory,and credible degree recognition criteria were established according to the unascertained measurement theory.The results of mining method evaluation were obtained using the credible degree criteria,thus the best underground mining method was determined.Furthermore,this model was employed for the comprehensive evaluation and selection of the chosen standard mining methods in Xinli Gold Mine in Sanshandao of China.The results show that the relative superiority degrees of mining methods can be calculated using the unascertained measurement optimization model,so the optimal method can be easily determined.Meanwhile,the proposed method can take into account large amount of uncertain information in mining method selection,which can provide an effective way for selecting the optimal underground mining method.
文摘To detect the DoS in networks by applying association rules mining techniques, we propose that association rules and frequent itemsets can be employed to find DoS pattern in packet streams which describe traffic and user behaviors. The method extracts information from the log analysis of submitted packets using the algorithm which depends on the definition of the intrusion. Large itemsets were extracted to represent the super facts to build the association analysis for the intrusion. Network data files were analysed for experiments. The analysis and experimental results are encouraging with better performance as packet frequency number increases.
