Ventilation system is significant in underground metal mine of alpine region.Reasonable evaluation of ventilation effectiveness will lead to a practical improvement for the maintenance and management of ventilation sy...Ventilation system is significant in underground metal mine of alpine region.Reasonable evaluation of ventilation effectiveness will lead to a practical improvement for the maintenance and management of ventilation system.However,it is difficult to make an effective evaluation of ventilation system due to the lack of classification criteria with respect to underground metal mine in alpine region.This paper proposes a novel evaluation method called the cloud model-clustering analysis(CMCA).Cloud model(CM)is utilized to process collected data of ventilation system,and they are converted into cloud descriptors by CM.Cloud similarity(CS)based Euclidean distance(ED)is proposed to make clustering analysis of assessed samples.Then the classification of assessed samples will be identified by clustering analysis results.A case study is developed based on CMCA.Evaluation results show that ventilation effectiveness can be well classified.Moreover,CM is used alone to make comparison of evaluation results obtained by CMCA.Then the availability and validity of CMCA is verified.Meanwhile,difference of CS based ED and classical ED is analyzed.Two new clustering analysis methods are introduced to make comparison with CMCA.Then the ability of proposed CMCA to meet evaluation requirements of ventilation system is verified.展开更多
Building a cloud geodatabase for a sponge city is crucial to integrate the geospatial information dispersed in various departments for multi-user high concurrent access and retrieval,high scalability and availability,...Building a cloud geodatabase for a sponge city is crucial to integrate the geospatial information dispersed in various departments for multi-user high concurrent access and retrieval,high scalability and availability,efficient storage and management.In this study,Hadoop distributed computing framework,including Hadoop distributed file system and MapReduce(mapper and reducer),is firstly designed with a parallel computing framework to process massive spatial data.Then,access control with a series of standard application programming interfaces for different functions is designed,including spatial data storage layer,cloud geodatabase access layer,spatial data access layer and spatial data analysis layer.Subsequently,a retrieval model is designed,including direct addressing via file name,three-level concurrent retrieval and block data retrieval strategies.Main functions are realised,including real-time concurrent access,high-performance computing,communication,massive data storage,efficient retrieval and scheduling decisions on the multi-scale,multi-source and massive spatial data.Finally,the performance of Hadoop cloud geodatabases is validated and compared with that of the Oracle database.The cloud geodatabase for the sponge city can avoid redundant configuration of personnel,hardware and software,support the data transfer,model debugging and application development,and provide accurate,real-time,virtual,intelligent,reliable,elastically scalable,dynamic and on-demand cloud services of the basic and thematic geographic information for the construction and management of the sponge city.展开更多
基金Project(2018YFC0808404)supported by National Key Research and Development Program of China。
文摘Ventilation system is significant in underground metal mine of alpine region.Reasonable evaluation of ventilation effectiveness will lead to a practical improvement for the maintenance and management of ventilation system.However,it is difficult to make an effective evaluation of ventilation system due to the lack of classification criteria with respect to underground metal mine in alpine region.This paper proposes a novel evaluation method called the cloud model-clustering analysis(CMCA).Cloud model(CM)is utilized to process collected data of ventilation system,and they are converted into cloud descriptors by CM.Cloud similarity(CS)based Euclidean distance(ED)is proposed to make clustering analysis of assessed samples.Then the classification of assessed samples will be identified by clustering analysis results.A case study is developed based on CMCA.Evaluation results show that ventilation effectiveness can be well classified.Moreover,CM is used alone to make comparison of evaluation results obtained by CMCA.Then the availability and validity of CMCA is verified.Meanwhile,difference of CS based ED and classical ED is analyzed.Two new clustering analysis methods are introduced to make comparison with CMCA.Then the ability of proposed CMCA to meet evaluation requirements of ventilation system is verified.
基金Project(NZ1628)supported by the Natural Science Foundation of Ningxia,China
文摘Building a cloud geodatabase for a sponge city is crucial to integrate the geospatial information dispersed in various departments for multi-user high concurrent access and retrieval,high scalability and availability,efficient storage and management.In this study,Hadoop distributed computing framework,including Hadoop distributed file system and MapReduce(mapper and reducer),is firstly designed with a parallel computing framework to process massive spatial data.Then,access control with a series of standard application programming interfaces for different functions is designed,including spatial data storage layer,cloud geodatabase access layer,spatial data access layer and spatial data analysis layer.Subsequently,a retrieval model is designed,including direct addressing via file name,three-level concurrent retrieval and block data retrieval strategies.Main functions are realised,including real-time concurrent access,high-performance computing,communication,massive data storage,efficient retrieval and scheduling decisions on the multi-scale,multi-source and massive spatial data.Finally,the performance of Hadoop cloud geodatabases is validated and compared with that of the Oracle database.The cloud geodatabase for the sponge city can avoid redundant configuration of personnel,hardware and software,support the data transfer,model debugging and application development,and provide accurate,real-time,virtual,intelligent,reliable,elastically scalable,dynamic and on-demand cloud services of the basic and thematic geographic information for the construction and management of the sponge city.
