Recently, attention has been focused on spatial query language which is used to query spatial databases. A design of spatial query language has been presented in this paper by extending the standard relational databas...Recently, attention has been focused on spatial query language which is used to query spatial databases. A design of spatial query language has been presented in this paper by extending the standard relational database query language SQL. It recognizes the significantly different requirements of spatial data handling and overcomes the inherent problems of the application of conventional database query languages. This design is based on an extended spatial data model, including the spatial data types and the spatial operators on them. The processing and optimization of spatial queries have also been discussed in this design. In the end, an implementation of this design is given in a spatial query subsystem.展开更多
Aiming at the problem that only some types of SPARQL （ simple protocal and resource description framework query language） queries can be answered by using the current resource description framework link traversal ba...Aiming at the problem that only some types of SPARQL （ simple protocal and resource description framework query language） queries can be answered by using the current resource description framework link traversal based query execution （RDF-LTE） approach, this paper discusses how the execution order of the triple pattern affects the query results and cost based on concrete SPARQL queries, and analyzes two properties of the web of linked data, missing backward links and missing contingency solution. Then three heuristic principles for logic query plan optimization, namely, the filtered basic graph pattern （FBGP） principle, the triple pattern chain principle and the seed URIs principle, are proposed. The three principles contribute to decrease the intermediate solutions and increase the types of queries that can be answered. The effectiveness and feasibility of the proposed approach is evaluated. The experimental results show that more query results can be returned with less cost, thus enabling users to develop the full potential of the web of linked data.展开更多
Accurately and efficiently predicting the permeability of porous media is essential for addressing a wide range of hydrogeological issues.However,the complexity of porous media often limits the effectiveness of indivi...Accurately and efficiently predicting the permeability of porous media is essential for addressing a wide range of hydrogeological issues.However,the complexity of porous media often limits the effectiveness of individual prediction methods.This study introduces a novel Particle Swarm Optimization-based Permeability Integrated Prediction model(PSO-PIP),which incorporates a particle swarm optimization algorithm enhanced with dy-namic clustering and adaptive parameter tuning(KGPSO).The model integrates multi-source data from the Lattice Boltzmann Method(LBM),Pore Network Modeling(PNM),and Finite Difference Method(FDM).By assigning optimal weight coefficients to the outputs of these methods,the model minimizes deviations from actual values and enhances permeability prediction performance.Initially,the computational performances of the LBM,PNM,and FDM are comparatively analyzed on datasets consisting of sphere packings and real rock samples.It is observed that these methods exhibit computational biases in certain permeability ranges.The PSOPIP model is proposed to combine the strengths of each computational approach and mitigate their limitations.The PSO-PIP model consistently produces predictions that are highly congruent with actual permeability values across all prediction intervals,significantly enhancing prediction accuracy.The outcomes of this study provide a new tool and perspective for the comprehensive,rapid,and accurate prediction of permeability in porous media.展开更多
The multidimensional analysis engine data management platform is constructed using big data distributed storage and parallel computing,data warehouse modeling technology,realizing the optimal management and instant qu...The multidimensional analysis engine data management platform is constructed using big data distributed storage and parallel computing,data warehouse modeling technology,realizing the optimal management and instant query of distributed oil and gas production dynamic big data.The centralized management and quick response of the production data of more than 36×10^4 oil,gas and water wells is realized.Multidimensional analysis subject model of oil,gas and water well production is built to pretreat the relevant data.At the level of China National Petroleum Corporation(CNPC),the rapid analysis and applications such as oil and gas production tracking,early production warning of key oilfields,analysis of low production wells and long shutdown wells,classification of reservoir development laws have been realized,and the processing time has been shortened from 1 d to 5 s.The basic unit of oil and gas production analysis is refined from oilfield to single well,making the production management more detailed.The process can be traced step by step according to CNPC,oil field company,field,block and single well,and the oil and gas production performance of each unit can be mastered in real time.展开更多
Join operation is a critical problem when dealing with sliding window over data streams. There have been many optimization strategies for sliding window join in the literature, but a simple heuristic is always used fo...Join operation is a critical problem when dealing with sliding window over data streams. There have been many optimization strategies for sliding window join in the literature, but a simple heuristic is always used for selecting the join sequence of many sliding windows, which is ineffectively. The graph-based approach is proposed to process the problem. The sliding window join model is introduced primarily. In this model vertex represent join operator and edge indicated the join relationship among sliding windows. Vertex weight and edge weight represent the cost of join and the reciprocity of join operators respectively. Then good query plan with minimal cost can be found in the model. Thus a complete join algorithm combining setting up model, finding optimal query plan and executing query plan is shown. Experiments show that the graph-based approach is feasible and can work better in above environment.展开更多
We developed a parallel object relational DBMS named PORLES. It uses BSP model as its parallel computing model, and monoid calculus as its basis of data model. In this paper, we introduce its data model, parallel que...We developed a parallel object relational DBMS named PORLES. It uses BSP model as its parallel computing model, and monoid calculus as its basis of data model. In this paper, we introduce its data model, parallel query optimization, transaction processing system and parallel access method in detail.展开更多
Quality traceability plays an essential role in assembling and welding offshore platform blocks.The improvement of the welding quality traceability system is conducive to improving the durability of the offshore platf...Quality traceability plays an essential role in assembling and welding offshore platform blocks.The improvement of the welding quality traceability system is conducive to improving the durability of the offshore platform and the process level of the offshore industry.Currently,qualitymanagement remains in the era of primary information,and there is a lack of effective tracking and recording of welding quality data.When welding defects are encountered,it is difficult to rapidly and accurately determine the root cause of the problem from various complexities and scattered quality data.In this paper,a composite welding quality traceability model for offshore platform block construction process is proposed,it contains the quality early-warning method based on long short-term memory and quality data backtracking query optimization algorithm.By fulfilling the training of the early-warning model and the implementation of the query optimization algorithm,the quality traceability model has the ability to assist enterprises in realizing the rapid identification and positioning of quality problems.Furthermore,the model and the quality traceability algorithm are checked by cases in actual working conditions.Verification analyses suggest that the proposed early-warningmodel for welding quality and the algorithmfor optimizing backtracking requests are effective and can be applied to the actual construction process.展开更多
基金This work is supported by the National High Technology Research and Development Program ofChina(2 0 0 2 AA135 2 30 ) and the Major Project of National Natural Science Foundation of Beijing(4 0 110 0 2 ) .
文摘Recently, attention has been focused on spatial query language which is used to query spatial databases. A design of spatial query language has been presented in this paper by extending the standard relational database query language SQL. It recognizes the significantly different requirements of spatial data handling and overcomes the inherent problems of the application of conventional database query languages. This design is based on an extended spatial data model, including the spatial data types and the spatial operators on them. The processing and optimization of spatial queries have also been discussed in this design. In the end, an implementation of this design is given in a spatial query subsystem.
基金The National Natural Science Foundation of China(No.61070170)the Natural Science Foundation of Higher Education Institutions of Jiangsu Province(No.11KJB520017)Suzhou Application Foundation Research Project(No.SYG201238)
文摘Aiming at the problem that only some types of SPARQL （ simple protocal and resource description framework query language） queries can be answered by using the current resource description framework link traversal based query execution （RDF-LTE） approach, this paper discusses how the execution order of the triple pattern affects the query results and cost based on concrete SPARQL queries, and analyzes two properties of the web of linked data, missing backward links and missing contingency solution. Then three heuristic principles for logic query plan optimization, namely, the filtered basic graph pattern （FBGP） principle, the triple pattern chain principle and the seed URIs principle, are proposed. The three principles contribute to decrease the intermediate solutions and increase the types of queries that can be answered. The effectiveness and feasibility of the proposed approach is evaluated. The experimental results show that more query results can be returned with less cost, thus enabling users to develop the full potential of the web of linked data.
基金supported by the National Key Research and Devel-opment Program of China (Grant No.2022YFC3005503)the National Natural Science Foundation of China (Grant Nos.52322907,52179141,U23B20149,U2340232)+1 种基金the Fundamental Research Funds for the Central Universities (Grant Nos.2042024kf1031,2042024kf0031)the Key Program of Science and Technology of Yunnan Province (Grant Nos.202202AF080004,202203AA080009).
文摘Accurately and efficiently predicting the permeability of porous media is essential for addressing a wide range of hydrogeological issues.However,the complexity of porous media often limits the effectiveness of individual prediction methods.This study introduces a novel Particle Swarm Optimization-based Permeability Integrated Prediction model(PSO-PIP),which incorporates a particle swarm optimization algorithm enhanced with dy-namic clustering and adaptive parameter tuning(KGPSO).The model integrates multi-source data from the Lattice Boltzmann Method(LBM),Pore Network Modeling(PNM),and Finite Difference Method(FDM).By assigning optimal weight coefficients to the outputs of these methods,the model minimizes deviations from actual values and enhances permeability prediction performance.Initially,the computational performances of the LBM,PNM,and FDM are comparatively analyzed on datasets consisting of sphere packings and real rock samples.It is observed that these methods exhibit computational biases in certain permeability ranges.The PSOPIP model is proposed to combine the strengths of each computational approach and mitigate their limitations.The PSO-PIP model consistently produces predictions that are highly congruent with actual permeability values across all prediction intervals,significantly enhancing prediction accuracy.The outcomes of this study provide a new tool and perspective for the comprehensive,rapid,and accurate prediction of permeability in porous media.
基金Supported by the China National Science and Technology Major Project(2016ZX05016-006).
文摘The multidimensional analysis engine data management platform is constructed using big data distributed storage and parallel computing,data warehouse modeling technology,realizing the optimal management and instant query of distributed oil and gas production dynamic big data.The centralized management and quick response of the production data of more than 36×10^4 oil,gas and water wells is realized.Multidimensional analysis subject model of oil,gas and water well production is built to pretreat the relevant data.At the level of China National Petroleum Corporation(CNPC),the rapid analysis and applications such as oil and gas production tracking,early production warning of key oilfields,analysis of low production wells and long shutdown wells,classification of reservoir development laws have been realized,and the processing time has been shortened from 1 d to 5 s.The basic unit of oil and gas production analysis is refined from oilfield to single well,making the production management more detailed.The process can be traced step by step according to CNPC,oil field company,field,block and single well,and the oil and gas production performance of each unit can be mastered in real time.
文摘Join operation is a critical problem when dealing with sliding window over data streams. There have been many optimization strategies for sliding window join in the literature, but a simple heuristic is always used for selecting the join sequence of many sliding windows, which is ineffectively. The graph-based approach is proposed to process the problem. The sliding window join model is introduced primarily. In this model vertex represent join operator and edge indicated the join relationship among sliding windows. Vertex weight and edge weight represent the cost of join and the reciprocity of join operators respectively. Then good query plan with minimal cost can be found in the model. Thus a complete join algorithm combining setting up model, finding optimal query plan and executing query plan is shown. Experiments show that the graph-based approach is feasible and can work better in above environment.
文摘We developed a parallel object relational DBMS named PORLES. It uses BSP model as its parallel computing model, and monoid calculus as its basis of data model. In this paper, we introduce its data model, parallel query optimization, transaction processing system and parallel access method in detail.
基金funded by Ministry of Industry and Information Technology of the People’s Republic of China[Grant No.2018473].
文摘Quality traceability plays an essential role in assembling and welding offshore platform blocks.The improvement of the welding quality traceability system is conducive to improving the durability of the offshore platform and the process level of the offshore industry.Currently,qualitymanagement remains in the era of primary information,and there is a lack of effective tracking and recording of welding quality data.When welding defects are encountered,it is difficult to rapidly and accurately determine the root cause of the problem from various complexities and scattered quality data.In this paper,a composite welding quality traceability model for offshore platform block construction process is proposed,it contains the quality early-warning method based on long short-term memory and quality data backtracking query optimization algorithm.By fulfilling the training of the early-warning model and the implementation of the query optimization algorithm,the quality traceability model has the ability to assist enterprises in realizing the rapid identification and positioning of quality problems.Furthermore,the model and the quality traceability algorithm are checked by cases in actual working conditions.Verification analyses suggest that the proposed early-warningmodel for welding quality and the algorithmfor optimizing backtracking requests are effective and can be applied to the actual construction process.
