In this work, we introduce a method of fingerprint directional image partitioning based on GA. According to the fingerprint topology, A set of dynamic partition masks and a cost estimating function are designed to gui...In this work, we introduce a method of fingerprint directional image partitioning based on GA. According to the fingerprint topology, A set of dynamic partition masks and a cost estimating function are designed to guide the partitioning procedure. Finding best fitted mask application is converted to an functional optimizing problem, and we give out a GA solution to the problem. At last, we discuss the application of the proposed method in Fingerprint Classification.展开更多
In order to solve the parallel algorithm of Petri net system with concurrent function, so as to achieve the parallel control and simulation operation of this system, this paper proposes the function partition complete...In order to solve the parallel algorithm of Petri net system with concurrent function, so as to achieve the parallel control and simulation operation of this system, this paper proposes the function partition completeness theory and algorithms of Petri net parallelization, thereby providing the theoretical support for the realization of Petri parallel algorithms. Firstly, according to the concurrent characteristics of Petri net model, we analyze the parallelism of Petri net system; then, by giving the solving process of place invariants and the function partitioning of Petri net, we propose the function partitioning conditions and determination theorem of Petri net parallelization, and conduct its theoretical proof and practical verification. On this basis, we conduct the theoretical study and analysis on the situation that Petri net system has several kinds of parallel function partitioning, propose the completeness theorem of parallelism function partitioning in Petri net system, and verify it. Finally, we give the algorithms, application examples and simulation experiment results of parallel function partitioning of Petri net systems based on place invariant. The theoretical proof and experimental results show that the function partitioning conditions and completeness theory of Petri net parallelization based on place invariant are correct, and the parallel algorithms under such theoretical basis are also correct and effective.展开更多
Hardware/software（HW/SW） partitioning is one of the key processes in an embedded system.It is used to determine which system components are assigned to hardware and which are processed by software.In contrast with p...Hardware/software（HW/SW） partitioning is one of the key processes in an embedded system.It is used to determine which system components are assigned to hardware and which are processed by software.In contrast with previous research that focuses on developing efficient heuristic,we focus on the pre-process of the task graph before the HW/SW partitioning in this paper,that is,enumerating all the sub-graphs that meet the requirements.Experimental results showed that the original graph can be reduced to 67% in the worst-case scenario and 58% in the best-case scenario.In conclusion,the reduced task graph saved hardware area while improving partitioning speed and accuracy.展开更多
Considering the defects of conventional optimization methods, a novel optimization algorithm is introduced in this paper. Target space partitioning method is used in this algorithm to solve multi-objective optimizatio...Considering the defects of conventional optimization methods, a novel optimization algorithm is introduced in this paper. Target space partitioning method is used in this algorithm to solve multi-objective optimization problem, thus achieve the coherent solution which can meet the requirements of all target functions, and improve the population's overall evolution level. The algorithm which guarantees diversity preservation and fast convergence to the Pareto set is applied to structural optimization problems. The empirical analysis supports the algorithm and gives an example with program.展开更多
This paper presents an algorithm that combines the chaos optimization algorithm with the maximum entropy ( COA-ME) by using entropy model based on chaos algorithm,in which the maximum entropy is used as the second met...This paper presents an algorithm that combines the chaos optimization algorithm with the maximum entropy ( COA-ME) by using entropy model based on chaos algorithm,in which the maximum entropy is used as the second method of searching the excellent solution. The search direction is improved by chaos optimization algorithm and realizes the selective acceptance of wrong solution. The experimental result shows that the presented algorithm can be used in the partitioning of hardware/software of reconfigurable system. It effectively reduces the local extremum problem,and search speed as well as performance of partitioning is improved.展开更多
Blockchain technology,with its attributes of decentralization,immutability,and traceability,has emerged as a powerful catalyst for enhancing traditional industries in terms of optimizing business processes.However,tra...Blockchain technology,with its attributes of decentralization,immutability,and traceability,has emerged as a powerful catalyst for enhancing traditional industries in terms of optimizing business processes.However,transaction performance and scalability has become the main challenges hindering the widespread adoption of blockchain.Due to its inability to meet the demands of high-frequency trading,blockchain cannot be adopted in many scenarios.To improve the transaction capacity,researchers have proposed some on-chain scaling technologies,including lightning networks,directed acyclic graph technology,state channels,and shardingmechanisms,inwhich sharding emerges as a potential scaling technology.Nevertheless,excessive cross-shard transactions and uneven shard workloads prevent the sharding mechanism from achieving the expected aim.This paper proposes a graphbased sharding scheme for public blockchain to efficiently balance the transaction distribution.Bymitigating crossshard transactions and evening-out workloads among shards,the scheme reduces transaction confirmation latency and enhances the transaction capacity of the blockchain.Therefore,the scheme can achieve a high-frequency transaction as well as a better blockchain scalability.Experiments results show that the scheme effectively reduces the cross-shard transaction ratio to a range of 35%-56%and significantly decreases the transaction confirmation latency to 6 s in a blockchain with no more than 25 shards.展开更多
Information about the relative importance of each criterion or theweights of criteria can have a significant influence on the ultimate rank of alternatives.Accordingly,assessing the weights of criteria is a very impor...Information about the relative importance of each criterion or theweights of criteria can have a significant influence on the ultimate rank of alternatives.Accordingly,assessing the weights of criteria is a very important task in solving multi-criteria decision-making problems.Three methods are commonly used for assessing the weights of criteria:objective,subjective,and integrated methods.In this study,an objective approach is proposed to assess the weights of criteria,called SPCmethod(Symmetry Point of Criterion).This point enriches the criterion so that it is balanced and easy to implement in the process of the evaluation of its influence on decision-making.The SPC methodology is systematically presented and supported by detailed calculations related to an artificial example.To validate the developed method,we used our numerical example and calculated the weights of criteria by CRITIC,Entropy,Standard Deviation and MEREC methods.Comparative analysis between these methods and the SPC method reveals that the developedmethod is a very reliable objective way to determine the weights of criteria.Additionally,in this study,we proposed the application of SPCmethod to evaluate the efficiency of themulti-criteria partitioning algorithm.The main idea of the evaluation is based on the following fact:the greater the uniformity of the weights of criteria,the higher the efficiency of the partitioning algorithm.The research demonstrates that the SPC method can be applied to solving different multi-criteria problems.展开更多
The implicit partition algorithm used to solve fluid–structure coupling problems has high accuracy,but it requires a long computation time.In this paper,a semi-implicit fluid–structure coupling algorithm based on mo...The implicit partition algorithm used to solve fluid–structure coupling problems has high accuracy,but it requires a long computation time.In this paper,a semi-implicit fluid–structure coupling algorithm based on modal force prediction-correction is proposed to improve the computational efficiency.In the pre-processing stage,the fluid domain is assumed to be a pseudo-elastic solid and merged with the solid domain to form a holistic system,and the normalized modal information of the holistic system is calculated and stored.During the sub-step cycle,the modal superposition method is used to obtain the response of the holistic system with the predicted modal force as the load,so that the deformation of the structure and the updating of the fluid mesh can be achieved simultaneously.After solving the Reynolds-averaged Navier-Stokes equations in the fluid domain,the predicted modal force is corrected and a new sub-step cycle is started until the converged result is obtained.In this method,the computation of the fluid equations and the updating of the dynamic mesh are done implicitly,while the deformation of the structure is done explicitly.Two numerical cases,vortex induced oscillation of an elastic beam and fluid–structure interaction of a final stage blade,are used to verify the efficiency and accuracy of the proposed algorithm.The results show that the proposed method achieves the same accuracy as the implicit method while the computational time is reduced.In the case of the vortex-induced oscillation problem,the computational time can be reduced to 18.6%.In the case of the final stage blade vibration,the computational time can be reduced to 53.8%.展开更多
With the large-scale integration of renewable energy sources into the grid,distribution networks are increasingly challenged by issues related to renewable energy accommodation and the mainte-nance of power quality st...With the large-scale integration of renewable energy sources into the grid,distribution networks are increasingly challenged by issues related to renewable energy accommodation and the mainte-nance of power quality stability.To address the challenge that existing partitioning methods are inad-equate for the planning and operation needs of active distribution networks under frequently changing power flow conditions,a three-stage dynamic partitioning approach is proposed based on an im-proved sand cat swarm optimization(ISCSO)algorithm.Firstly,a comprehensive dynamic partitio-ning index is developed by integrating both structural and functional metrics,including modularity,voltage regulation capability,and regional renewable energy accommodation capacity.Secondly,to overcome the limitations of the conventional sand cat swarm optimization,namely its weak global ex-ploration ability and tendency to fall into local optima in the later optimization stages,chaotic map-ping is employed to initialize a uniformly distributed population.A nonlinear sensitivity mechanism is introduced to balance global exploration and local exploitation,alongside the design of a particle encoding and position updating scheme tailored for dynamic partitioning.Furthermore,a‘state re-tention-local adjustment-global reconstruction’partitioning structure is developed.To avoid unnec-essary partition changes under minor source-load fluctuations,the concept of overlapping nodes is introduced,enabling fine-tuned adjustments under such conditions.Finally,two experimental sce-narios are designed to validate the proposed method.Simulation results demonstrate strong electrical coupling performance and show that the method enhances voltage regulation and renewable energy integration capabilities across regions.展开更多
To overcome some drawbacks of Viterbi algorithm （VA）, such as exponential growing complexity of decoding, and its poor performance under bad channel conditions, some available known information must be used as cons...To overcome some drawbacks of Viterbi algorithm （VA）, such as exponential growing complexity of decoding, and its poor performance under bad channel conditions, some available known information must be used as constrained condition and apriori knowledge for decoding. A new constrained VA is proposed by adding con- straint bits directly for conventional codec. Compared with the conventional VA, under the bad channel condi- tion, the proposed scheme can improve the peak signal to noise ratio （PSNR） of the decoding image 2--10 dB by changing the number of constrained bits. Experimental results show that it is an efficient error-controlling way for the transmission of set partitioning in hierarchical trees （SPIHT） coded image.展开更多
Early water breakthrough and a rapid increase in water cut are always observed in high- permeability completion intervals when perforations are uniformly distributed in the wellbore in heterogeneous reservoirs. Optimi...Early water breakthrough and a rapid increase in water cut are always observed in high- permeability completion intervals when perforations are uniformly distributed in the wellbore in heterogeneous reservoirs. Optimization of perforating parameters in partitioned sections in horizontal intervals helps homogenize the inflow from the reservoir and thus is critically important for enhanced oil recovery. This paper derives a coupled reservoir-wellbore flow model based on inflow controlling theory. Genetic algorithms are applied to solving the model as they excel in obtaining the global optimum of discrete functions. The optimized perforating strategy applies a low perforation density in high- permeability intervals and a high perforation density in low-permeability intervals. As a result, the inflow profile is homogenized and idealized.展开更多
Region partition(RP) is the key technique to the finite element parallel computing(FEPC),and its performance has a decisive influence on the entire process of analysis and computation.The performance evaluation index ...Region partition(RP) is the key technique to the finite element parallel computing(FEPC),and its performance has a decisive influence on the entire process of analysis and computation.The performance evaluation index of RP method for the three-dimensional finite element model(FEM) has been given.By taking the electric field of aluminum reduction cell(ARC) as the research object,the performance of two classical RP methods,which are Al-NASRA and NGUYEN partition(ANP) algorithm and the multi-level partition(MLP) method,has been analyzed and compared.The comparison results indicate a sound performance of ANP algorithm,but to large-scale models,the computing time of ANP algorithm increases notably.This is because the ANP algorithm determines only one node based on the minimum weight and just adds the elements connected to the node into the sub-region during each iteration.To obtain the satisfied speed and the precision,an improved dynamic self-adaptive ANP(DSA-ANP) algorithm has been proposed.With consideration of model scale,complexity and sub-RP stage,the improved algorithm adaptively determines the number of nodes and selects those nodes with small enough weight,and then dynamically adds these connected elements.The proposed algorithm has been applied to the finite element analysis(FEA) of the electric field simulation of ARC.Compared with the traditional ANP algorithm,the computational efficiency of the proposed algorithm has been shortened approximately from 260 s to 13 s.This proves the superiority of the improved algorithm on computing time performance.展开更多
The development of algebraic and numerical algorithms is a kind of complicated creative work and it is difficult to guarantee the correctness of the algorithms. This paper introduces a systematic and unified formal de...The development of algebraic and numerical algorithms is a kind of complicated creative work and it is difficult to guarantee the correctness of the algorithms. This paper introduces a systematic and unified formal development method of algebraic and numerical algorithms. The method implements the complete refinement process from abstract specifications to a concrete executable program. It uses the core idea of partition and recursion for formal derivation and combines the mathematical induction based on strict mathematical logic with Hoare axiom for correctness verification. This development method converts creative work into non-creative work as much as possible while ensuring the correctness of the algorithm, which can not only verify the correctness of the existing algebraic and numerical algorithms but also guide the development of efficient unknown algorithms for such problems. This paper takes the non-recursive implementation of the Extended Euclidean Algorithm and Horner's method as examples. Therefore, the effectiveness and feasibility of this method are further verified.展开更多
The increasing overlap of core and colony populations during the anaphase of evolution may limit the performance of shifting balance genetic algorithms. To decrease such overlapping,so as to increase the local search ...The increasing overlap of core and colony populations during the anaphase of evolution may limit the performance of shifting balance genetic algorithms. To decrease such overlapping,so as to increase the local search capability of the core population,the sub-space method was used to generate uniformly distributed initial colony populations over the decision variable space. The core population was also dynamically divided,making simultaneous searching in several local spaces possible. The algorithm proposed in this paper was compared to the original one by searching for the optimum of a complicated multi-modal function. The results indicate that the solutions obtained by the modified algorithm are better than those of the original algorithm.展开更多
With the development of global position system（GPS）,wireless technology and location aware services,it is possible to collect a large quantity of trajectory data.In the field of data mining for moving objects,the pr...With the development of global position system（GPS）,wireless technology and location aware services,it is possible to collect a large quantity of trajectory data.In the field of data mining for moving objects,the problem of anomaly detection is a hot topic.Based on the development of anomalous trajectory detection of moving objects,this paper introduces the classical trajectory outlier detection（TRAOD） algorithm,and then proposes a density-based trajectory outlier detection（DBTOD） algorithm,which compensates the disadvantages of the TRAOD algorithm that it is unable to detect anomalous defects when the trajectory is local and dense.The results of employing the proposed algorithm to Elk1993 and Deer1995 datasets are also presented,which show the effectiveness of the algorithm.展开更多
In this paper we develop modeling techniques for a social partitioning problem. Different social interaction regulations are imposed during pandemics to prevent the spread of diseases. We suggest partitioning a set of...In this paper we develop modeling techniques for a social partitioning problem. Different social interaction regulations are imposed during pandemics to prevent the spread of diseases. We suggest partitioning a set of company employees as an effective way to curb the spread, and use integer programming techniques to model it. The goal of the model is to maximize the number of direct interactions between employees who are essential for company’s work subject to the constraint that all employees should be partitioned into components of no more than a certain size implied by the regulations. Then we further develop the basic model to take into account different restrictions and provisions. We also give heuristics for solving the problem. Our computational results include sensitivity analysis on some of the models and analysis of the heuristic performance.展开更多
To determine CDN cache servers'placement reasonably,an idea that using graph partitioning to solve the problem was put forward through theoretical analysis and the specific algorithm of partitioning was researched...To determine CDN cache servers'placement reasonably,an idea that using graph partitioning to solve the problem was put forward through theoretical analysis and the specific algorithm of partitioning was researched. The concept of graph partitioning for CDN was defined. The conditions of graph partitioning for CDN were demonstrated: the sum of the weights of the nodes in each subarea is as close as possible; edge cut between the subareas is as large as possible; internal nodes in each subarea are connected as far as possible. By reference to light vertex matching algorithm of graph partitioning for network simulation,a multilevel k-way algorithm of graph partitioning for CDN was proposed. The maximized edge cut k-way KL refinement algorithm was discussed. Graph partitioning is a feasible way to solve the problem of CDN servers'placement. Multilevel k-way algorithm is a feasible algorithm for CDN graph partitioning.展开更多
In this paper, the storage capacity of communication among cores and processors is taken into account and a maximum D-value-first algorithm is proposed. By improving the hardware parallelism in the task execution proc...In this paper, the storage capacity of communication among cores and processors is taken into account and a maximum D-value-first algorithm is proposed. By improving the hardware parallelism in the task execution process, the maximum storage requirements for communication are minimized. Experimental results with various directed acyclic graph models showed that compared with the earliest-task-first algorithm, the storage requirements for communication were reduced by 22.46%, on average, while the average of makespan only increased by 0.82%,.展开更多
Many real-world networks are found to be scale-free. However, graph partition technology, as a technology capable of parallel computing, performs poorly when scale-free graphs are provided. The reason for this is that...Many real-world networks are found to be scale-free. However, graph partition technology, as a technology capable of parallel computing, performs poorly when scale-free graphs are provided. The reason for this is that traditional partitioning algorithms are designed for random networks and regular networks, rather than for scale-free networks. Multilevel graph-partitioning algorithms are currently considered to be the state of the art and are used extensively. In this paper, we analyse the reasons why traditional multilevel graph-partitioning algorithms perform poorly and present a new multilevel graph-partitioning paradigm, top down partitioning, which derives its name from the comparison with the traditional bottom-up partitioning. A new multilevel partitioning algorithm, named betweenness-based partitioning algorithm, is also presented as an implementation of top-down partitioning paradigm. An experimental evaluation of seven different real-world scale-free networks shows that the betweenness-based partitioning algorithm significantly outperforms the existing state-of-the-art approaches.展开更多
Based on the full domain partition, a parallel finite element algorithm for the stationary Stokes equations is proposed and analyzed. In this algorithm, each subproblem is defined in the entire domain. Majority of the...Based on the full domain partition, a parallel finite element algorithm for the stationary Stokes equations is proposed and analyzed. In this algorithm, each subproblem is defined in the entire domain. Majority of the degrees of freedom are associated with the relevant subdomain. Therefore, it can be solved in parallel with other subproblems using an existing sequential solver without extensive recoding. This allows the algorithm to be implemented easily with low communication costs. Numerical results are given showing the high efficiency of the parallel algorithm.展开更多
文摘In this work, we introduce a method of fingerprint directional image partitioning based on GA. According to the fingerprint topology, A set of dynamic partition masks and a cost estimating function are designed to guide the partitioning procedure. Finding best fitted mask application is converted to an functional optimizing problem, and we give out a GA solution to the problem. At last, we discuss the application of the proposed method in Fingerprint Classification.
基金Supported by the National Natural Science Foundation of China(61866006,61741203)the Natural Science Foundation of Guangxi Province(2016GXNSFAA380243)+1 种基金the Guangxi Innovation-Driven Development of Special Funds Project(Gui Ke AA17204091)the Guangxi Nanning Science and Technology Development Planning Project(2018015-5)
文摘In order to solve the parallel algorithm of Petri net system with concurrent function, so as to achieve the parallel control and simulation operation of this system, this paper proposes the function partition completeness theory and algorithms of Petri net parallelization, thereby providing the theoretical support for the realization of Petri parallel algorithms. Firstly, according to the concurrent characteristics of Petri net model, we analyze the parallelism of Petri net system; then, by giving the solving process of place invariants and the function partitioning of Petri net, we propose the function partitioning conditions and determination theorem of Petri net parallelization, and conduct its theoretical proof and practical verification. On this basis, we conduct the theoretical study and analysis on the situation that Petri net system has several kinds of parallel function partitioning, propose the completeness theorem of parallelism function partitioning in Petri net system, and verify it. Finally, we give the algorithms, application examples and simulation experiment results of parallel function partitioning of Petri net systems based on place invariant. The theoretical proof and experimental results show that the function partitioning conditions and completeness theory of Petri net parallelization based on place invariant are correct, and the parallel algorithms under such theoretical basis are also correct and effective.
基金Supported by the National Natural Science Foundation of China (60970016,61173032)
文摘Hardware/software（HW/SW） partitioning is one of the key processes in an embedded system.It is used to determine which system components are assigned to hardware and which are processed by software.In contrast with previous research that focuses on developing efficient heuristic,we focus on the pre-process of the task graph before the HW/SW partitioning in this paper,that is,enumerating all the sub-graphs that meet the requirements.Experimental results showed that the original graph can be reduced to 67% in the worst-case scenario and 58% in the best-case scenario.In conclusion,the reduced task graph saved hardware area while improving partitioning speed and accuracy.
基金National Natural Science Foundations of China (No. 60970004, No. 60743010)Natural Science Foundation of ShandongProvince, China (No. Z2008G02)
文摘Considering the defects of conventional optimization methods, a novel optimization algorithm is introduced in this paper. Target space partitioning method is used in this algorithm to solve multi-objective optimization problem, thus achieve the coherent solution which can meet the requirements of all target functions, and improve the population's overall evolution level. The algorithm which guarantees diversity preservation and fast convergence to the Pareto set is applied to structural optimization problems. The empirical analysis supports the algorithm and gives an example with program.
基金Sponsored by the Natural Science Foundation of Heilongjiang Province( Grant No B2007-07)Industrial Research Projects in Qiqihaer( Grant No GYGG-09009)
文摘This paper presents an algorithm that combines the chaos optimization algorithm with the maximum entropy ( COA-ME) by using entropy model based on chaos algorithm,in which the maximum entropy is used as the second method of searching the excellent solution. The search direction is improved by chaos optimization algorithm and realizes the selective acceptance of wrong solution. The experimental result shows that the presented algorithm can be used in the partitioning of hardware/software of reconfigurable system. It effectively reduces the local extremum problem,and search speed as well as performance of partitioning is improved.
基金supported by Shandong Provincial Key Research and Development Program of China(2021CXGC010107,2020CXGC010107)the Shandong Provincial Natural Science Foundation of China(ZR2020KF035)the New 20 Project of Higher Education of Jinan,China(202228017).
文摘Blockchain technology,with its attributes of decentralization,immutability,and traceability,has emerged as a powerful catalyst for enhancing traditional industries in terms of optimizing business processes.However,transaction performance and scalability has become the main challenges hindering the widespread adoption of blockchain.Due to its inability to meet the demands of high-frequency trading,blockchain cannot be adopted in many scenarios.To improve the transaction capacity,researchers have proposed some on-chain scaling technologies,including lightning networks,directed acyclic graph technology,state channels,and shardingmechanisms,inwhich sharding emerges as a potential scaling technology.Nevertheless,excessive cross-shard transactions and uneven shard workloads prevent the sharding mechanism from achieving the expected aim.This paper proposes a graphbased sharding scheme for public blockchain to efficiently balance the transaction distribution.Bymitigating crossshard transactions and evening-out workloads among shards,the scheme reduces transaction confirmation latency and enhances the transaction capacity of the blockchain.Therefore,the scheme can achieve a high-frequency transaction as well as a better blockchain scalability.Experiments results show that the scheme effectively reduces the cross-shard transaction ratio to a range of 35%-56%and significantly decreases the transaction confirmation latency to 6 s in a blockchain with no more than 25 shards.
文摘Information about the relative importance of each criterion or theweights of criteria can have a significant influence on the ultimate rank of alternatives.Accordingly,assessing the weights of criteria is a very important task in solving multi-criteria decision-making problems.Three methods are commonly used for assessing the weights of criteria:objective,subjective,and integrated methods.In this study,an objective approach is proposed to assess the weights of criteria,called SPCmethod(Symmetry Point of Criterion).This point enriches the criterion so that it is balanced and easy to implement in the process of the evaluation of its influence on decision-making.The SPC methodology is systematically presented and supported by detailed calculations related to an artificial example.To validate the developed method,we used our numerical example and calculated the weights of criteria by CRITIC,Entropy,Standard Deviation and MEREC methods.Comparative analysis between these methods and the SPC method reveals that the developedmethod is a very reliable objective way to determine the weights of criteria.Additionally,in this study,we proposed the application of SPCmethod to evaluate the efficiency of themulti-criteria partitioning algorithm.The main idea of the evaluation is based on the following fact:the greater the uniformity of the weights of criteria,the higher the efficiency of the partitioning algorithm.The research demonstrates that the SPC method can be applied to solving different multi-criteria problems.
基金support of the National Natural Science Foundation of China(No.51675406)the Basic Research Project Group,China(No.514010106-205)。
文摘The implicit partition algorithm used to solve fluid–structure coupling problems has high accuracy,but it requires a long computation time.In this paper,a semi-implicit fluid–structure coupling algorithm based on modal force prediction-correction is proposed to improve the computational efficiency.In the pre-processing stage,the fluid domain is assumed to be a pseudo-elastic solid and merged with the solid domain to form a holistic system,and the normalized modal information of the holistic system is calculated and stored.During the sub-step cycle,the modal superposition method is used to obtain the response of the holistic system with the predicted modal force as the load,so that the deformation of the structure and the updating of the fluid mesh can be achieved simultaneously.After solving the Reynolds-averaged Navier-Stokes equations in the fluid domain,the predicted modal force is corrected and a new sub-step cycle is started until the converged result is obtained.In this method,the computation of the fluid equations and the updating of the dynamic mesh are done implicitly,while the deformation of the structure is done explicitly.Two numerical cases,vortex induced oscillation of an elastic beam and fluid–structure interaction of a final stage blade,are used to verify the efficiency and accuracy of the proposed algorithm.The results show that the proposed method achieves the same accuracy as the implicit method while the computational time is reduced.In the case of the vortex-induced oscillation problem,the computational time can be reduced to 18.6%.In the case of the final stage blade vibration,the computational time can be reduced to 53.8%.
基金Supported by the Technology Project of State Grid Corporation Headquarters(No.5100-202322029A-1-1-ZN)the 2024 Youth Science Foun-dation Project(No.62303006).
文摘With the large-scale integration of renewable energy sources into the grid,distribution networks are increasingly challenged by issues related to renewable energy accommodation and the mainte-nance of power quality stability.To address the challenge that existing partitioning methods are inad-equate for the planning and operation needs of active distribution networks under frequently changing power flow conditions,a three-stage dynamic partitioning approach is proposed based on an im-proved sand cat swarm optimization(ISCSO)algorithm.Firstly,a comprehensive dynamic partitio-ning index is developed by integrating both structural and functional metrics,including modularity,voltage regulation capability,and regional renewable energy accommodation capacity.Secondly,to overcome the limitations of the conventional sand cat swarm optimization,namely its weak global ex-ploration ability and tendency to fall into local optima in the later optimization stages,chaotic map-ping is employed to initialize a uniformly distributed population.A nonlinear sensitivity mechanism is introduced to balance global exploration and local exploitation,alongside the design of a particle encoding and position updating scheme tailored for dynamic partitioning.Furthermore,a‘state re-tention-local adjustment-global reconstruction’partitioning structure is developed.To avoid unnec-essary partition changes under minor source-load fluctuations,the concept of overlapping nodes is introduced,enabling fine-tuned adjustments under such conditions.Finally,two experimental sce-narios are designed to validate the proposed method.Simulation results demonstrate strong electrical coupling performance and show that the method enhances voltage regulation and renewable energy integration capabilities across regions.
文摘To overcome some drawbacks of Viterbi algorithm （VA）, such as exponential growing complexity of decoding, and its poor performance under bad channel conditions, some available known information must be used as constrained condition and apriori knowledge for decoding. A new constrained VA is proposed by adding con- straint bits directly for conventional codec. Compared with the conventional VA, under the bad channel condi- tion, the proposed scheme can improve the peak signal to noise ratio （PSNR） of the decoding image 2--10 dB by changing the number of constrained bits. Experimental results show that it is an efficient error-controlling way for the transmission of set partitioning in hierarchical trees （SPIHT） coded image.
基金supported by National Scientific Project(No. 2008ZX05024-03)
文摘Early water breakthrough and a rapid increase in water cut are always observed in high- permeability completion intervals when perforations are uniformly distributed in the wellbore in heterogeneous reservoirs. Optimization of perforating parameters in partitioned sections in horizontal intervals helps homogenize the inflow from the reservoir and thus is critically important for enhanced oil recovery. This paper derives a coupled reservoir-wellbore flow model based on inflow controlling theory. Genetic algorithms are applied to solving the model as they excel in obtaining the global optimum of discrete functions. The optimized perforating strategy applies a low perforation density in high- permeability intervals and a high perforation density in low-permeability intervals. As a result, the inflow profile is homogenized and idealized.
基金Project(61273187)supported by the National Natural Science Foundation of ChinaProject(61321003)supported by the Foundation for Innovative Research Groups of the National Natural Science Foundation of China
文摘Region partition(RP) is the key technique to the finite element parallel computing(FEPC),and its performance has a decisive influence on the entire process of analysis and computation.The performance evaluation index of RP method for the three-dimensional finite element model(FEM) has been given.By taking the electric field of aluminum reduction cell(ARC) as the research object,the performance of two classical RP methods,which are Al-NASRA and NGUYEN partition(ANP) algorithm and the multi-level partition(MLP) method,has been analyzed and compared.The comparison results indicate a sound performance of ANP algorithm,but to large-scale models,the computing time of ANP algorithm increases notably.This is because the ANP algorithm determines only one node based on the minimum weight and just adds the elements connected to the node into the sub-region during each iteration.To obtain the satisfied speed and the precision,an improved dynamic self-adaptive ANP(DSA-ANP) algorithm has been proposed.With consideration of model scale,complexity and sub-RP stage,the improved algorithm adaptively determines the number of nodes and selects those nodes with small enough weight,and then dynamically adds these connected elements.The proposed algorithm has been applied to the finite element analysis(FEA) of the electric field simulation of ARC.Compared with the traditional ANP algorithm,the computational efficiency of the proposed algorithm has been shortened approximately from 260 s to 13 s.This proves the superiority of the improved algorithm on computing time performance.
基金Supported by the National Natural Science Foundation of China (61862033, 61762049, 61902162)Jiangxi Provincial Natural Science Foundation (20202BABL202026, 20202BABL202025, 20202BAB202015)。
文摘The development of algebraic and numerical algorithms is a kind of complicated creative work and it is difficult to guarantee the correctness of the algorithms. This paper introduces a systematic and unified formal development method of algebraic and numerical algorithms. The method implements the complete refinement process from abstract specifications to a concrete executable program. It uses the core idea of partition and recursion for formal derivation and combines the mathematical induction based on strict mathematical logic with Hoare axiom for correctness verification. This development method converts creative work into non-creative work as much as possible while ensuring the correctness of the algorithm, which can not only verify the correctness of the existing algebraic and numerical algorithms but also guide the development of efficient unknown algorithms for such problems. This paper takes the non-recursive implementation of the Extended Euclidean Algorithm and Horner's method as examples. Therefore, the effectiveness and feasibility of this method are further verified.
基金Project 60575046 supported by the National Natural Science Foundation of China
文摘The increasing overlap of core and colony populations during the anaphase of evolution may limit the performance of shifting balance genetic algorithms. To decrease such overlapping,so as to increase the local search capability of the core population,the sub-space method was used to generate uniformly distributed initial colony populations over the decision variable space. The core population was also dynamically divided,making simultaneous searching in several local spaces possible. The algorithm proposed in this paper was compared to the original one by searching for the optimum of a complicated multi-modal function. The results indicate that the solutions obtained by the modified algorithm are better than those of the original algorithm.
基金supported by the Aeronautical Science Foundation of China(20111052010)the Jiangsu Graduates Innovation Project (CXZZ120163)+1 种基金the "333" Project of Jiangsu Provincethe Qing Lan Project of Jiangsu Province
文摘With the development of global position system（GPS）,wireless technology and location aware services,it is possible to collect a large quantity of trajectory data.In the field of data mining for moving objects,the problem of anomaly detection is a hot topic.Based on the development of anomalous trajectory detection of moving objects,this paper introduces the classical trajectory outlier detection（TRAOD） algorithm,and then proposes a density-based trajectory outlier detection（DBTOD） algorithm,which compensates the disadvantages of the TRAOD algorithm that it is unable to detect anomalous defects when the trajectory is local and dense.The results of employing the proposed algorithm to Elk1993 and Deer1995 datasets are also presented,which show the effectiveness of the algorithm.
文摘In this paper we develop modeling techniques for a social partitioning problem. Different social interaction regulations are imposed during pandemics to prevent the spread of diseases. We suggest partitioning a set of company employees as an effective way to curb the spread, and use integer programming techniques to model it. The goal of the model is to maximize the number of direct interactions between employees who are essential for company’s work subject to the constraint that all employees should be partitioned into components of no more than a certain size implied by the regulations. Then we further develop the basic model to take into account different restrictions and provisions. We also give heuristics for solving the problem. Our computational results include sensitivity analysis on some of the models and analysis of the heuristic performance.
基金Sponsored by the National Natural Science Foundation of China(Grant No.60973027)Science Projects of China National Ministry of Information Industry(Grant No.01XK230009)
文摘To determine CDN cache servers'placement reasonably,an idea that using graph partitioning to solve the problem was put forward through theoretical analysis and the specific algorithm of partitioning was researched. The concept of graph partitioning for CDN was defined. The conditions of graph partitioning for CDN were demonstrated: the sum of the weights of the nodes in each subarea is as close as possible; edge cut between the subareas is as large as possible; internal nodes in each subarea are connected as far as possible. By reference to light vertex matching algorithm of graph partitioning for network simulation,a multilevel k-way algorithm of graph partitioning for CDN was proposed. The maximized edge cut k-way KL refinement algorithm was discussed. Graph partitioning is a feasible way to solve the problem of CDN servers'placement. Multilevel k-way algorithm is a feasible algorithm for CDN graph partitioning.
基金Supported by the National Natural Science Foundation of China(No.61179045 and No.61350009)
文摘In this paper, the storage capacity of communication among cores and processors is taken into account and a maximum D-value-first algorithm is proposed. By improving the hardware parallelism in the task execution process, the maximum storage requirements for communication are minimized. Experimental results with various directed acyclic graph models showed that compared with the earliest-task-first algorithm, the storage requirements for communication were reduced by 22.46%, on average, while the average of makespan only increased by 0.82%,.
基金supported by the National Science Foundation for Distinguished Young Scholars of China(Grant Nos.61003082 and 60903059)the National Natural Science Foundation of China(Grant No.60873014)the Foundation for Innovative Research Groups of the National Natural Science Foundation of China(Grant No.60921062)
文摘Many real-world networks are found to be scale-free. However, graph partition technology, as a technology capable of parallel computing, performs poorly when scale-free graphs are provided. The reason for this is that traditional partitioning algorithms are designed for random networks and regular networks, rather than for scale-free networks. Multilevel graph-partitioning algorithms are currently considered to be the state of the art and are used extensively. In this paper, we analyse the reasons why traditional multilevel graph-partitioning algorithms perform poorly and present a new multilevel graph-partitioning paradigm, top down partitioning, which derives its name from the comparison with the traditional bottom-up partitioning. A new multilevel partitioning algorithm, named betweenness-based partitioning algorithm, is also presented as an implementation of top-down partitioning paradigm. An experimental evaluation of seven different real-world scale-free networks shows that the betweenness-based partitioning algorithm significantly outperforms the existing state-of-the-art approaches.
基金Project supported by the National Natural Science Foundation of China (No.10971166)the National Basic Research Program (No.2005CB321703)the Science and Technology Foundation of Guizhou Province of China (No.[2008]2123)
文摘Based on the full domain partition, a parallel finite element algorithm for the stationary Stokes equations is proposed and analyzed. In this algorithm, each subproblem is defined in the entire domain. Majority of the degrees of freedom are associated with the relevant subdomain. Therefore, it can be solved in parallel with other subproblems using an existing sequential solver without extensive recoding. This allows the algorithm to be implemented easily with low communication costs. Numerical results are given showing the high efficiency of the parallel algorithm.
