The presence of numerous uncertainties in hybrid decision information systems(HDISs)renders attribute reduction a formidable task.Currently available attribute reduction algorithms,including those based on Pawlak attr...The presence of numerous uncertainties in hybrid decision information systems(HDISs)renders attribute reduction a formidable task.Currently available attribute reduction algorithms,including those based on Pawlak attribute importance,Skowron discernibility matrix,and information entropy,struggle to effectively manages multiple uncertainties simultaneously in HDISs like the precise measurement of disparities between nominal attribute values,and attributes with fuzzy boundaries and abnormal values.In order to address the aforementioned issues,this paper delves into the study of attribute reduction withinHDISs.First of all,a novel metric based on the decision attribute is introduced to solve the problem of accurately measuring the differences between nominal attribute values.The newly introduced distance metric has been christened the supervised distance that can effectively quantify the differences between the nominal attribute values.Then,based on the newly developed metric,a novel fuzzy relationship is defined from the perspective of“feedback on parity of attribute values to attribute sets”.This new fuzzy relationship serves as a valuable tool in addressing the challenges posed by abnormal attribute values.Furthermore,leveraging the newly introduced fuzzy relationship,the fuzzy conditional information entropy is defined as a solution to the challenges posed by fuzzy attributes.It effectively quantifies the uncertainty associated with fuzzy attribute values,thereby providing a robust framework for handling fuzzy information in hybrid information systems.Finally,an algorithm for attribute reduction utilizing the fuzzy conditional information entropy is presented.The experimental results on 12 datasets show that the average reduction rate of our algorithm reaches 84.04%,and the classification accuracy is improved by 3.91%compared to the original dataset,and by an average of 11.25%compared to the other 9 state-of-the-art reduction algorithms.The comprehensive analysis of these research results clearly indicates that our algorithm is highly effective in managing the intricate uncertainties inherent in hybrid data.展开更多
Rod milling sand(RMS)—a coarse sand aggregate—was recycled for cemented paste backfill(CPB)for the underground mined area at the Jinchuan nickel deposit,named rod milling sand-based cemented paste backfill(RCPB).The...Rod milling sand(RMS)—a coarse sand aggregate—was recycled for cemented paste backfill(CPB)for the underground mined area at the Jinchuan nickel deposit,named rod milling sand-based cemented paste backfill(RCPB).The adverse effects of coarse particles on the transportation of CPB slurry through pipelines to underground stopes resulting in weakening of the stability of the backfill system are well known.Therefore,sulfonated naphthalene formaldehyde(SNF)condensate was used for the performance improvement of RCPB.The synergistic effect of solid content(SC),lime-to-sand ratio,and SNF dosage on the rheological and physicomechanical properties,including slump,yield stress,bleeding rate,uniaxial compressive strength(UCS),as well as mechanism analysis of RCPB,have been explored.The results indicate that the effect of SNF on RCPB performance is related to the SNF dosage,lime-to-sand ratio,and SC.The slump of fresh RCPB with 0.1wt%-0.5wt%SNF increased by 2.6%-26.2%,whereas the yield stress reduced by 4.1%-50.3%,indicating better workability and improved cohesiveness of the mix.The bleeding rate of fresh RCPB decreased first and then rose with the increase of SNF dosage,and the peak decrease was 67.67%.UCS of RCPB first increased and then decreased with the increase of SNF dosage.At the optimal SNF addition ratio of 0.3wt%,the UCS of RCPB curing for 7,14 and,28 d ages increased by 31.5%,28.4%,and 29.5%,respectively.The beneficial effects of SNF in enhancing the early UCS of RCPB have been corroborated.However,the later UCS increases at a slower rate.The research findings may guide the design and preparation of RCPB with adequate performance for practical applications.展开更多
Pipeline hydraulic transport is a highly efficient and low energy-consumption method for transporting solids and is commonly used for tailing slurry transport in the mining industry.Erosion wear(EW)remains the main ca...Pipeline hydraulic transport is a highly efficient and low energy-consumption method for transporting solids and is commonly used for tailing slurry transport in the mining industry.Erosion wear(EW)remains the main cause of failure in tailings slurry pipeline systems,particularly at bends.EW is a complex phenomenon influenced by numerous factors,but research in this area has been limited.This study performs numerical simulations of slurry transport at the bend by combining computational fluid dynamics and fluid particle tracking using a wear model.Based on the validation of the feasibility of the model,this work focuses on the effects of coupled inlet velocity(IV)ranging from 1.5 to 3.0 m·s^(-1),particle size(PS)ranging from 50 to 650μm,and bend angle(BA)ranging from 45°to 90°on EW at the bend in terms of particle kinetic energy and incidence angle.The results show that the maximum EW rate of the slurry at the bend increases exponentially with IV and PS and first increases and then decreases with the increase in BA with the inflection point at 60°within these parameter ranges.Further comprehensive analysis reveals that the sensitivity level of the three factors to the maximum EW rate is PS>IV>BA,and when IV is 3.0 m/s,PS is 650μm,and BA is 60°,the bend EW is the most severe,and the maximum EW rate is 5.68×10^(-6)kg·m^(-2)·s^(-1).In addition,When PS is below or equal to 450μm,the maximum EW position is mainly at the outlet of the bend.When PS is greater than 450μm,the maximum EW position shifts toward the center of the bend with the increase in BA.Therefore,EW at the bend can be reduced in practice by reducing IV as much as possible and using small particles.展开更多
基金Anhui Province Natural Science Research Project of Colleges and Universities(2023AH040321)Excellent Scientific Research and Innovation Team of Anhui Colleges(2022AH010098).
文摘The presence of numerous uncertainties in hybrid decision information systems(HDISs)renders attribute reduction a formidable task.Currently available attribute reduction algorithms,including those based on Pawlak attribute importance,Skowron discernibility matrix,and information entropy,struggle to effectively manages multiple uncertainties simultaneously in HDISs like the precise measurement of disparities between nominal attribute values,and attributes with fuzzy boundaries and abnormal values.In order to address the aforementioned issues,this paper delves into the study of attribute reduction withinHDISs.First of all,a novel metric based on the decision attribute is introduced to solve the problem of accurately measuring the differences between nominal attribute values.The newly introduced distance metric has been christened the supervised distance that can effectively quantify the differences between the nominal attribute values.Then,based on the newly developed metric,a novel fuzzy relationship is defined from the perspective of“feedback on parity of attribute values to attribute sets”.This new fuzzy relationship serves as a valuable tool in addressing the challenges posed by abnormal attribute values.Furthermore,leveraging the newly introduced fuzzy relationship,the fuzzy conditional information entropy is defined as a solution to the challenges posed by fuzzy attributes.It effectively quantifies the uncertainty associated with fuzzy attribute values,thereby providing a robust framework for handling fuzzy information in hybrid information systems.Finally,an algorithm for attribute reduction utilizing the fuzzy conditional information entropy is presented.The experimental results on 12 datasets show that the average reduction rate of our algorithm reaches 84.04%,and the classification accuracy is improved by 3.91%compared to the original dataset,and by an average of 11.25%compared to the other 9 state-of-the-art reduction algorithms.The comprehensive analysis of these research results clearly indicates that our algorithm is highly effective in managing the intricate uncertainties inherent in hybrid data.
基金financially supported by the National Natural Science Foundation of China(Nos.52104156,52074351,52004330)the Science and Technology Innovation Program of Hunan Province,China(No.2021RC3125)the Natural Science Foundation of Hunan Province,China(No.2022JJ30714)。
文摘Rod milling sand(RMS)—a coarse sand aggregate—was recycled for cemented paste backfill(CPB)for the underground mined area at the Jinchuan nickel deposit,named rod milling sand-based cemented paste backfill(RCPB).The adverse effects of coarse particles on the transportation of CPB slurry through pipelines to underground stopes resulting in weakening of the stability of the backfill system are well known.Therefore,sulfonated naphthalene formaldehyde(SNF)condensate was used for the performance improvement of RCPB.The synergistic effect of solid content(SC),lime-to-sand ratio,and SNF dosage on the rheological and physicomechanical properties,including slump,yield stress,bleeding rate,uniaxial compressive strength(UCS),as well as mechanism analysis of RCPB,have been explored.The results indicate that the effect of SNF on RCPB performance is related to the SNF dosage,lime-to-sand ratio,and SC.The slump of fresh RCPB with 0.1wt%-0.5wt%SNF increased by 2.6%-26.2%,whereas the yield stress reduced by 4.1%-50.3%,indicating better workability and improved cohesiveness of the mix.The bleeding rate of fresh RCPB decreased first and then rose with the increase of SNF dosage,and the peak decrease was 67.67%.UCS of RCPB first increased and then decreased with the increase of SNF dosage.At the optimal SNF addition ratio of 0.3wt%,the UCS of RCPB curing for 7,14 and,28 d ages increased by 31.5%,28.4%,and 29.5%,respectively.The beneficial effects of SNF in enhancing the early UCS of RCPB have been corroborated.However,the later UCS increases at a slower rate.The research findings may guide the design and preparation of RCPB with adequate performance for practical applications.
基金financially supported by the National Natural Science Foundation of China (Nos.52104156,52074351 and 52004330)the Science and Technology Innovation Program of Hunan Province,China (No.2021RC3125).
文摘Pipeline hydraulic transport is a highly efficient and low energy-consumption method for transporting solids and is commonly used for tailing slurry transport in the mining industry.Erosion wear(EW)remains the main cause of failure in tailings slurry pipeline systems,particularly at bends.EW is a complex phenomenon influenced by numerous factors,but research in this area has been limited.This study performs numerical simulations of slurry transport at the bend by combining computational fluid dynamics and fluid particle tracking using a wear model.Based on the validation of the feasibility of the model,this work focuses on the effects of coupled inlet velocity(IV)ranging from 1.5 to 3.0 m·s^(-1),particle size(PS)ranging from 50 to 650μm,and bend angle(BA)ranging from 45°to 90°on EW at the bend in terms of particle kinetic energy and incidence angle.The results show that the maximum EW rate of the slurry at the bend increases exponentially with IV and PS and first increases and then decreases with the increase in BA with the inflection point at 60°within these parameter ranges.Further comprehensive analysis reveals that the sensitivity level of the three factors to the maximum EW rate is PS>IV>BA,and when IV is 3.0 m/s,PS is 650μm,and BA is 60°,the bend EW is the most severe,and the maximum EW rate is 5.68×10^(-6)kg·m^(-2)·s^(-1).In addition,When PS is below or equal to 450μm,the maximum EW position is mainly at the outlet of the bend.When PS is greater than 450μm,the maximum EW position shifts toward the center of the bend with the increase in BA.Therefore,EW at the bend can be reduced in practice by reducing IV as much as possible and using small particles.
