Based on the rough set theory which is a powerful tool in dealing with vagueness and uncertainty, an algorithm to mine association rules in incomplete information systems was presented and the support and confidence w...Based on the rough set theory which is a powerful tool in dealing with vagueness and uncertainty, an algorithm to mine association rules in incomplete information systems was presented and the support and confidence were redefined. The algorithm can mine the association rules with decision attributes directly without processing missing values. Using the incomplete dataset Mushroom from UCI machine learning repository, the new algorithm was compared with the classical association rules mining algorithm based on Apriori from the number of rules extracted, testing accuracy and execution time. The experiment results show that the new algorithm has advantages of short execution time and high accuracy.展开更多
Focusing on the issue to deal with inadequate extraction of metallogenic information especially geological information,a new method of extracting metallogenic information based on field model,i.e.the field analysis me...Focusing on the issue to deal with inadequate extraction of metallogenic information especially geological information,a new method of extracting metallogenic information based on field model,i.e.the field analysis method of metallogenic information,was proposed.In addition,a case study by using the method of the extraction of metallogenic information from the west Guangxi and southeast Yunnan district as an example was performed.The representation method for the field models of metallogenic information,including the metallogenic influence field model and the metallogenic distance field model,was discussed by introducing the concept of the field theory,based on the characteristic analysis of the distance gradualness and the influence superposition of metallogenic information.According to the field theory superposition principle and the spatial distance analysis method,the mathematical models for the metallogenic influence field and the metallogenic distance field of point,line and area geological bodies were derived out by using parameter equation and calculus.Based on the metallogenic background analysis,the metallogenic information field models of synsedimentary faults and manganese sedimentary basins were built.The relationship between the metallogenic information fields and the manganese mineralization distribution was also investigated by using the method of metallogenic information field analysis.The instance study indicates that the proposed method of metallogenic information field analysis is valid and useful for extracting the ore-controlling information of synsedimentary faults and manganese sedimentary basins in the study area,with which the extraction results are significant both statistically and geologically.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
基金Projects(10871031, 60474070) supported by the National Natural Science Foundation of ChinaProject(07A001) supported by the Scientific Research Fund of Hunan Provincial Education Department, China
文摘Based on the rough set theory which is a powerful tool in dealing with vagueness and uncertainty, an algorithm to mine association rules in incomplete information systems was presented and the support and confidence were redefined. The algorithm can mine the association rules with decision attributes directly without processing missing values. Using the incomplete dataset Mushroom from UCI machine learning repository, the new algorithm was compared with the classical association rules mining algorithm based on Apriori from the number of rules extracted, testing accuracy and execution time. The experiment results show that the new algorithm has advantages of short execution time and high accuracy.
基金Project(2006BAB01B07) supported by the National Science and Technology Pillar Program during the 11th Five-Year Plan Period of China
文摘Focusing on the issue to deal with inadequate extraction of metallogenic information especially geological information,a new method of extracting metallogenic information based on field model,i.e.the field analysis method of metallogenic information,was proposed.In addition,a case study by using the method of the extraction of metallogenic information from the west Guangxi and southeast Yunnan district as an example was performed.The representation method for the field models of metallogenic information,including the metallogenic influence field model and the metallogenic distance field model,was discussed by introducing the concept of the field theory,based on the characteristic analysis of the distance gradualness and the influence superposition of metallogenic information.According to the field theory superposition principle and the spatial distance analysis method,the mathematical models for the metallogenic influence field and the metallogenic distance field of point,line and area geological bodies were derived out by using parameter equation and calculus.Based on the metallogenic background analysis,the metallogenic information field models of synsedimentary faults and manganese sedimentary basins were built.The relationship between the metallogenic information fields and the manganese mineralization distribution was also investigated by using the method of metallogenic information field analysis.The instance study indicates that the proposed method of metallogenic information field analysis is valid and useful for extracting the ore-controlling information of synsedimentary faults and manganese sedimentary basins in the study area,with which the extraction results are significant both statistically and geologically.
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.
